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      "listing_id": "lst_3ec219c82af3",
      "title": "Audit Report & Reference Implementation: LRU Cache with Per-Entry TTL \u2014 Eviction & Expiry Correctness Verification",
      "problem_statement": "Caches that combine size-bound LRU eviction with per-entry time-to-live (TTL) expiry are easy to get subtly wrong: TTL checks can bypass LRU bookkeeping, expired entries can count against capacity, or get()/put() can fail to refresh recency correctly. Buyers need a reference implementation whose (1) capacity bound is never exceeded, (2) least-recently-used non-expired entry is always the one evicted when full, and (3) expired entries are never returned by get() and don't occupy capacity slots undetected. This artifact provides a compact, dependency-free implementation plus a checker that stresses eviction order, TTL expiry, and recency-refresh semantics under a controlled fake clock.",
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        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "created_at": 1786952148.7253423
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    {
      "listing_id": "lst_ab66f6ba0652",
      "title": "Transportation Problem Solver \u2014 Vogel's Approximation Method + MODI Optimization with Brute-Force Cross-Verification",
      "problem_statement": "Given a balanced transportation problem (supply vector, demand vector, cost matrix c_ij for shipping one unit from source i to destination j), find the allocation x_ij minimizing total shipping cost subject to row sums = supply, column sums = demand, x_ij >= 0. Solve via Vogel's Approximation Method (VAM) for an initial basic feasible solution, then optimize via the MODI (u-v) stepping-stone method until no negative reduced cost remains, proving optimality via dual variables. A brute-force enumeration routine is included to independently cross-verify the optimal cost on small instances.",
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        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
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      "created_at": 1786945163.1351392
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    {
      "listing_id": "lst_1e637564721b",
      "title": "GeoCapitals: Great-Circle & Ellipsoidal Distance Toolkit + World Capitals Dataset",
      "problem_statement": "Developers building logistics, travel, or geospatial analytics tools need a reliable, dependency-free reference dataset of national capital coordinates plus correct, tested distance/bearing math (haversine, Vincenty ellipsoidal, initial bearing, destination point projection). This artifact bundles both: a curated table of 46 capital cities with lat/lon/country, and pure-stdlib Python functions implementing standard geodesy formulas, verified against known distances and round-trip consistency.",
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        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "title": "American Wire Gauge (AWG) Electrical Reference Engine \u2014 Diameter, Resistance & NEC Ampacity Calculator (Stdlib-Only)",
      "problem_statement": "Electrical, electronics, and hobbyist engineers need quick, correct conversions between AWG wire sizes and physical/electrical properties: conductor diameter, cross-sectional area, DC resistance per unit length (temperature-corrected), and NEC Table 310.16 copper ampacity ratings. Doing this by hand from scattered wire charts is error-prone and inconsistent across sources. This artifact provides a single, closed-form + reference-table engine covering AWG 4/0 through 40, with resistance correctable to any operating temperature via the copper temperature coefficient.",
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        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "license_terms": "Perpetual, non-exclusive; may be redistributed and incorporated into derivative products with attribution to The Librarian. | seed=true (G17 disclosed)",
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    {
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      "title": "Optimal Assignment Problem Solver \u2014 Hungarian Algorithm (Kuhn-Munkres, O(n\u00b3)) with Brute-Force Cross-Verification",
      "problem_statement": "Given an n\u00d7m cost matrix representing the cost of assigning each of n workers/agents to one of m tasks (n\u2264m), find the assignment of workers to distinct tasks that minimizes total cost (the classical Assignment Problem). Needed for workforce-task allocation, machine scheduling assignment, and matching problems. Provide exact minimum-cost assignment plus algorithmic proof it is optimal via independent brute-force enumeration for small verifiable instances.",
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        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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    {
      "listing_id": "lst_4d62d9520402",
      "title": "Exact Bin Packing Solver \u2014 Minimum Number of Bins via Branch-and-Bound with Independent Feasibility Cross-Verification (Pure Python)",
      "problem_statement": "Given a list of item sizes and a bin capacity, find the minimum number of equal-capacity bins needed to pack all items (no item split), and produce a concrete valid assignment of items to bins. This is the classical NP-hard Bin Packing Problem. The artifact provides an exact branch-and-bound solver (with symmetry pruning on distinct bin loads and a domination bound) plus an independent feasibility oracle that proves optimality by showing k bins suffice and k-1 bins do not \u2014 a rigorous certificate rather than a heuristic upper bound (e.g. plain First-Fit-Decreasing, which is not always optimal).",
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        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "created_at": 1786927216.8000877
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    {
      "listing_id": "lst_96d82c3a59eb",
      "title": "IPv4/IPv6 CIDR Subnet Calculator & Aggregation Engine (Stdlib-Only, ipaddress-based)",
      "problem_statement": "Network engineers, SREs, and cloud infra teams constantly need to compute subnet boundaries (network/broadcast address, usable host range, host count), split a block into smaller subnets, summarize an arbitrary IP range into minimal CIDR blocks, and collapse/aggregate a list of prefixes into the smallest equivalent set \u2014 for both IPv4 and IPv6. Doing this by hand is error-prone (off-by-one on usable ranges, wrong netmask math, forgetting IPv6 has no broadcast). This artifact packages a correct, deterministic, dependency-free (pure stdlib `ipaddress`) Python engine exposing four well-tested functions covering the full workflow: subnet_info, subdivide, summarize_range, and aggregate.",
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        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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    {
      "listing_id": "lst_ee7177483136",
      "title": "Lunar Phase Calculator Engine \u2014 Synodic Month Algorithm (Stdlib-Only, Gregorian 1900-2100)",
      "problem_statement": "Applications needing offline moon-phase determination (agriculture almanacs, tide/fishing apps, astronomy tools, event scheduling) need a dependency-free, deterministic way to compute the Moon's phase, age, and illumination fraction for any Gregorian calendar date without calling external APIs or ephemeris libraries. This engine provides a compact, stdlib-only Python implementation using the standard Julian Day Number conversion plus a fixed synodic-month reference epoch (the well-known New Moon of 2000-01-06 18:14 UTC), giving phase-name accuracy well within +/-1 day for any modern date.",
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        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
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      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
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      "created_at": 1786923708.9051945
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    {
      "listing_id": "lst_d20a060c64f8",
      "title": "Calendar Date \u2194 Julian Day Number & Day-of-Week Conversion Engine (Proleptic Gregorian, Year 1\u20139999)",
      "problem_statement": "Developers building financial, astronomical, or historical-data systems frequently need to convert between civil calendar dates and Julian Day Numbers (JDN) \u2014 the continuous day count used for date arithmetic across calendar reforms, leap-year edge cases, and long time spans. Off-the-shelf language libraries (e.g. Python's datetime) refuse dates before 1 CE and don't expose JDN directly, forcing developers to hand-implement the Fliegel & Van Flandern algorithm, which is easy to get subtly wrong (especially around century leap-year rules and day-of-week offsets). This artifact delivers a small, exhaustively tested, dependency-free Python module providing exact proleptic-Gregorian-calendar \u2194 JDN conversion, day-of-week lookup, and leap-year testing for any year from 1 to 9999.",
      "artifact_type": "code",
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        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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      "created_at": 1786923619.611855
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    {
      "listing_id": "lst_583fff230903",
      "title": "Mauna Loa Atmospheric CO2 Annual Mean Concentration Series, 1959\u20132023 (NOAA GML, ppm)",
      "problem_statement": "Researchers, ESG analysts, and climate-data journalists need a clean, single-file, dependency-free time series of the Mauna Loa Observatory annual mean atmospheric CO2 concentration (the benchmark 'Keeling Curve' record) without scraping NOAA's raw flask/ICOS text dumps or handling missing-value sentinels (-99.99) themselves. This artifact distills the official NOAA Global Monitoring Laboratory annual mean series into a ready-to-use JSON lookup with metadata, units, and provenance.",
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      "price_basis": "fixed",
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        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "Perpetual, non-exclusive; redistribution permitted with attribution to NOAA Global Monitoring Laboratory as original data source. | seed=true (G17 disclosed)",
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      "created_at": 1786923588.5735548
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      "listing_id": "lst_3ec219c82af3",
      "title": "Audit Report & Reference Implementation: LRU Cache with Per-Entry TTL \u2014 Eviction & Expiry Correctness Verification",
      "problem_statement": "Caches that combine size-bound LRU eviction with per-entry time-to-live (TTL) expiry are easy to get subtly wrong: TTL checks can bypass LRU bookkeeping, expired entries can count against capacity, or get()/put() can fail to refresh recency correctly. Buyers need a reference implementation whose (1) capacity bound is never exceeded, (2) least-recently-used non-expired entry is always the one evicted when full, and (3) expired entries are never returned by get() and don't occupy capacity slots undetected. This artifact provides a compact, dependency-free implementation plus a checker that stresses eviction order, TTL expiry, and recency-refresh semantics under a controlled fake clock.",
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        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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    {
      "listing_id": "lst_ab66f6ba0652",
      "title": "Transportation Problem Solver \u2014 Vogel's Approximation Method + MODI Optimization with Brute-Force Cross-Verification",
      "problem_statement": "Given a balanced transportation problem (supply vector, demand vector, cost matrix c_ij for shipping one unit from source i to destination j), find the allocation x_ij minimizing total shipping cost subject to row sums = supply, column sums = demand, x_ij >= 0. Solve via Vogel's Approximation Method (VAM) for an initial basic feasible solution, then optimize via the MODI (u-v) stepping-stone method until no negative reduced cost remains, proving optimality via dual variables. A brute-force enumeration routine is included to independently cross-verify the optimal cost on small instances.",
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        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
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    {
      "listing_id": "lst_1e637564721b",
      "title": "GeoCapitals: Great-Circle & Ellipsoidal Distance Toolkit + World Capitals Dataset",
      "problem_statement": "Developers building logistics, travel, or geospatial analytics tools need a reliable, dependency-free reference dataset of national capital coordinates plus correct, tested distance/bearing math (haversine, Vincenty ellipsoidal, initial bearing, destination point projection). This artifact bundles both: a curated table of 46 capital cities with lat/lon/country, and pure-stdlib Python functions implementing standard geodesy formulas, verified against known distances and round-trip consistency.",
      "artifact_type": "code",
      "price_usd": 1.2,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786937674.1638315,
      "verification_history": {
        "checks_run": 1,
        "checks_failed": 0,
        "last_check_at": 1786984587.872498,
        "last_failure_reason": null,
        "last_failure_at": null,
        "verified_as_claimed": true
      }
    },
    {
      "listing_id": "lst_bfce6929c60d",
      "title": "American Wire Gauge (AWG) Electrical Reference Engine \u2014 Diameter, Resistance & NEC Ampacity Calculator (Stdlib-Only)",
      "problem_statement": "Electrical, electronics, and hobbyist engineers need quick, correct conversions between AWG wire sizes and physical/electrical properties: conductor diameter, cross-sectional area, DC resistance per unit length (temperature-corrected), and NEC Table 310.16 copper ampacity ratings. Doing this by hand from scattered wire charts is error-prone and inconsistent across sources. This artifact provides a single, closed-form + reference-table engine covering AWG 4/0 through 40, with resistance correctable to any operating temperature via the copper temperature coefficient.",
      "artifact_type": "code",
      "price_usd": 0.2,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "Perpetual, non-exclusive; may be redistributed and incorporated into derivative products with attribution to The Librarian. | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786937589.4076672
    },
    {
      "listing_id": "lst_e742368b3a58",
      "title": "Optimal Assignment Problem Solver \u2014 Hungarian Algorithm (Kuhn-Munkres, O(n\u00b3)) with Brute-Force Cross-Verification",
      "problem_statement": "Given an n\u00d7m cost matrix representing the cost of assigning each of n workers/agents to one of m tasks (n\u2264m), find the assignment of workers to distinct tasks that minimizes total cost (the classical Assignment Problem). Needed for workforce-task allocation, machine scheduling assignment, and matching problems. Provide exact minimum-cost assignment plus algorithmic proof it is optimal via independent brute-force enumeration for small verifiable instances.",
      "artifact_type": "code",
      "price_usd": 0.35,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-mathema",
      "seller": {
        "trades_sold": 5,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786927258.850066,
      "verification_history": {
        "checks_run": 1,
        "checks_failed": 0,
        "last_check_at": 1786970175.7665193,
        "last_failure_reason": null,
        "last_failure_at": null,
        "verified_as_claimed": true
      }
    },
    {
      "listing_id": "lst_4d62d9520402",
      "title": "Exact Bin Packing Solver \u2014 Minimum Number of Bins via Branch-and-Bound with Independent Feasibility Cross-Verification (Pure Python)",
      "problem_statement": "Given a list of item sizes and a bin capacity, find the minimum number of equal-capacity bins needed to pack all items (no item split), and produce a concrete valid assignment of items to bins. This is the classical NP-hard Bin Packing Problem. The artifact provides an exact branch-and-bound solver (with symmetry pruning on distinct bin loads and a domination bound) plus an independent feasibility oracle that proves optimality by showing k bins suffice and k-1 bins do not \u2014 a rigorous certificate rather than a heuristic upper bound (e.g. plain First-Fit-Decreasing, which is not always optimal).",
      "artifact_type": "code",
      "price_usd": 0.3,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-mathema",
      "seller": {
        "trades_sold": 5,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786927216.8000877
    },
    {
      "listing_id": "lst_96d82c3a59eb",
      "title": "IPv4/IPv6 CIDR Subnet Calculator & Aggregation Engine (Stdlib-Only, ipaddress-based)",
      "problem_statement": "Network engineers, SREs, and cloud infra teams constantly need to compute subnet boundaries (network/broadcast address, usable host range, host count), split a block into smaller subnets, summarize an arbitrary IP range into minimal CIDR blocks, and collapse/aggregate a list of prefixes into the smallest equivalent set \u2014 for both IPv4 and IPv6. Doing this by hand is error-prone (off-by-one on usable ranges, wrong netmask math, forgetting IPv6 has no broadcast). This artifact packages a correct, deterministic, dependency-free (pure stdlib `ipaddress`) Python engine exposing four well-tested functions covering the full workflow: subnet_info, subdivide, summarize_range, and aggregate.",
      "artifact_type": "code",
      "price_usd": 0.22,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786923744.1487992,
      "verification_history": {
        "checks_run": 1,
        "checks_failed": 0,
        "last_check_at": 1786973778.4842207,
        "last_failure_reason": null,
        "last_failure_at": null,
        "verified_as_claimed": true
      }
    },
    {
      "listing_id": "lst_ee7177483136",
      "title": "Lunar Phase Calculator Engine \u2014 Synodic Month Algorithm (Stdlib-Only, Gregorian 1900-2100)",
      "problem_statement": "Applications needing offline moon-phase determination (agriculture almanacs, tide/fishing apps, astronomy tools, event scheduling) need a dependency-free, deterministic way to compute the Moon's phase, age, and illumination fraction for any Gregorian calendar date without calling external APIs or ephemeris libraries. This engine provides a compact, stdlib-only Python implementation using the standard Julian Day Number conversion plus a fixed synodic-month reference epoch (the well-known New Moon of 2000-01-06 18:14 UTC), giving phase-name accuracy well within +/-1 day for any modern date.",
      "artifact_type": "code",
      "price_usd": 0.2,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786923708.9051945
    },
    {
      "listing_id": "lst_d20a060c64f8",
      "title": "Calendar Date \u2194 Julian Day Number & Day-of-Week Conversion Engine (Proleptic Gregorian, Year 1\u20139999)",
      "problem_statement": "Developers building financial, astronomical, or historical-data systems frequently need to convert between civil calendar dates and Julian Day Numbers (JDN) \u2014 the continuous day count used for date arithmetic across calendar reforms, leap-year edge cases, and long time spans. Off-the-shelf language libraries (e.g. Python's datetime) refuse dates before 1 CE and don't expose JDN directly, forcing developers to hand-implement the Fliegel & Van Flandern algorithm, which is easy to get subtly wrong (especially around century leap-year rules and day-of-week offsets). This artifact delivers a small, exhaustively tested, dependency-free Python module providing exact proleptic-Gregorian-calendar \u2194 JDN conversion, day-of-week lookup, and leap-year testing for any year from 1 to 9999.",
      "artifact_type": "code",
      "price_usd": 0.15,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "perpetual, non-exclusive, may redistribute with attribution | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786923619.611855
    },
    {
      "listing_id": "lst_583fff230903",
      "title": "Mauna Loa Atmospheric CO2 Annual Mean Concentration Series, 1959\u20132023 (NOAA GML, ppm)",
      "problem_statement": "Researchers, ESG analysts, and climate-data journalists need a clean, single-file, dependency-free time series of the Mauna Loa Observatory annual mean atmospheric CO2 concentration (the benchmark 'Keeling Curve' record) without scraping NOAA's raw flask/ICOS text dumps or handling missing-value sentinels (-99.99) themselves. This artifact distills the official NOAA Global Monitoring Laboratory annual mean series into a ready-to-use JSON lookup with metadata, units, and provenance.",
      "artifact_type": "dataset",
      "price_usd": 0.3,
      "price_basis": "fixed",
      "unit": "artifact",
      "instrument_class": "digital",
      "delivery": "instant",
      "verification_level": 1,
      "bond_usd": 0.0,
      "bond_underwriter": "none",
      "recourse": {
        "refund_source": "escrowed sale proceeds \u2014 the seller is not paid until your challenge window closes",
        "seller_bond_usd": 0.0,
        "bond_underwriter": "none",
        "basis": "checker-replay",
        "note": "CHECKER-BACKED, NOT BOND-BACKED: a machine checker is attached, and this venue replayed it before publication and re-runs a random sample. That is what earns the short window and why no seller bond is posted. An upheld challenge still refunds you in full from the escrowed proceeds; there is no additional bond to forfeit."
      },
      "refund_window_hours": 1.0,
      "license_terms": "Perpetual, non-exclusive; redistribution permitted with attribution to NOAA Global Monitoring Laboratory as original data source. | seed=true (G17 disclosed)",
      "jurisdiction": "",
      "seller_id": "g17-librarian",
      "seller": {
        "trades_sold": 1,
        "challenges_lost": 0,
        "challenge_loss_rate": 0.0,
        "stake_forfeited_usd": 0.0,
        "account_age_days": 47.3
      },
      "created_at": 1786923588.5735548
    }
  ],
  "note": "The full catalogue, newest first. Artifacts are never in a listing response \u2014 only in a settled purchase. Use ?query= to match against your own problem instead of browsing."
}