benchmark-archaeology

Research

Evaluation Methodology Archaeology Campaign — 5 strategies for systematic analysis of AI/ML benchmarks, metrics, and leaderboards. Reveals construct validity issues, saturation, data contamination, and evaluation protocol inconsistencies.

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Benchmark Archaeology

Systematic excavation and critical analysis of AI/ML evaluation methodology. Treats benchmarks as historical artifacts requiring forensic examination — uncovering hidden assumptions, methodological drift, validity decay, and coverage gaps that accumulate over time.

Strategy Routing

Signal	Route To
"audit this benchmark", "benchmark quality", "BetterBench"	benchmark-audit
"saturation", "ceiling", "score plateau", "when will X be solved"	saturation-analysis
"does it actually measure", "construct validity", "what does score mean"	validity-probing
"what's not tested", "coverage gaps", "missing capabilities"	coverage-mapping
"different papers get different scores", "protocol differences"	protocol-forensics

Manifest

Strategies (5)

Strategy	Purpose
benchmark-audit	Systematic quality assessment using BetterBench 46-criterion framework
saturation-analysis	Track score trajectories, detect saturation and failure points
validity-probing	Challenge construct validity — does benchmark measure claimed capability?
coverage-mapping	Map evaluation coverage, identify untested capability dimensions
protocol-forensics	Analyze evaluation protocol differences across papers for same benchmark

Tactics (3)

Tactic	Purpose
score-trajectory-analysis	Collect historical scores, fit saturation curves, detect inflection points
artifact-detection	Detect annotation artifacts and shortcuts in benchmarks
evaluation-protocol-comparison	Compare implementation differences of same benchmark across papers

Subagent SOPs (9 + 1 shared)

SOP	Purpose
benchmark-inventory	Identify and catalog all relevant benchmarks in target domain
metric-decomposition	Decompose composite metrics into constituent signals
contamination-audit	Detect train-test data leakage and memorization artifacts
construct-validity-assessment	Evaluate whether benchmark measures its claimed capability
documentation-audit	Assess documentation completeness against BetterBench/Datasheets standards
capability-taxonomy-mapping	Build capability taxonomy, map existing benchmark coverage
leaderboard-dynamics-analysis	Analyze leaderboard score distributions, compression, selective reporting
protocol-element-extraction	Extract evaluation protocol parameters from papers
benchmark-synthesis	Produce final structured audit report
saturation-detection (shared)	Detect saturation signals in score trajectories (from literature-survey)

Budget Table

Strategy	Benchmarks	Papers	Web Searches
benchmark-audit	5	30	40
saturation-analysis	15	50	60
validity-probing	3	40	30
coverage-mapping	20	30	50
protocol-forensics	5	60	30
Total	48	210	210

MCP Tools

MCP Server	Tools
brave-search	brave_web_search, brave_llm_context
apify	rag-web-browser, google-scholar-scraper
alphaxiv	get_paper_content, answer_pdf_queries
semantic-scholar	ss_paper, ss_relevance_search, ss_citations, ss_references

Context Management

All outputs write to context/benchmark-archaeology/:

context/benchmark-archaeology/
  audit/              # benchmark-audit outputs
  saturation/         # saturation-analysis outputs
  validity/           # validity-probing outputs
  coverage/           # coverage-mapping outputs
  forensics/          # protocol-forensics outputs
  synthesis/          # Final cross-strategy synthesis

Each strategy maintains its own state ledger within its output directory.

Available Strategies

Optional, no fixed order; the final leaf is always a sop.

Strategy	When to use
benchmark-audit	Systematic quality assessment using BetterBench 46-criterion framework — 5 benchmarks, 30 papers, 40 web searches
coverage-mapping	Map evaluation coverage, identify untested capability dimensions — 20 benchmarks, 30 papers, 50 web searches
protocol-forensics	Analyze evaluation protocol differences across papers for same benchmark — 5 benchmarks, 60 papers, 30 web searches
saturation-analysis	Track score trajectories, detect saturation/failure points — 15 benchmarks, 50 papers, 60 web searches
validity-probing	Challenge construct validity — does benchmark measure claimed capability? — 3 benchmarks, 40 papers, 30 web searches

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
context-checkpoint	Append research process and results to the current Phase's context file. Each append MUST contain >=500 lines of markdown covering both process and results. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase.
context-init	Create a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed.