Corpus maps this to AGENTS.md as a compact routing table, structured docs, and background quality agents that scan for stale docs.
Tool profile · provisional profile
OpenAI harness engineering
Important evidence that compact routing files plus progressive disclosure can beat stuffing everything into context.
Provisional fit
75/100
Best for: Teams designing agent-readable repo instructions, docs routing, and background checks for stale guidance.
Avoid if: you need a fully governed, citation-complete knowledge architecture without adding policy, evidence capture, and review workflow around the tool.
Caution: It is an engineering pattern, not a packaged memory system. Capture and cross-team knowledge sharing still need surrounding workflow.
Model signature: Activation primary · repo/team scope · Engineering pattern
Layer coverage
Where this tool fits.
This is not a completed review. It is a provisional profile from public positioning plus known failure-mode mapping. Hands-on benchmarks, source snapshots, and citation-bound claims are still required before stronger conclusions.
Production
Curation
Storage
Activation
Governance
Review rule: a tool does not get credit for a layer unless it exposes inspectable behavior, not just a marketing claim.
Evidence notes
What the provisional profile has applied so far.
Latest research emphasizes activation: getting the right artifact into the right run with budget and authority constraints.
Needs review against repo diversity, stale-doc detection accuracy, and whether guidance gets promoted into code or tests.
Review packet
What a complete review must contain.
This page exposes the intended review structure. The current artifact is a profile, not a completed evidence-backed review.
Canonical source
Strengths
Teams designing agent-readable repo instructions, docs routing, and background checks for stale guidance.
Limitations
It is an engineering pattern, not a packaged memory system. Capture and cross-team knowledge sharing still need surrounding workflow.
Dimension assessment
Scope, volatility, authority, lifecycle, resource economics, interoperability, and evidence quality must each get a rationale and citations before final scoring.
Open questions
- What can be verified from docs, code, issues, benchmarks, and changelogs?
- Where does the tool fail under stale, contradictory, private, or high-cost knowledge?
- Which claims are vendor claims versus independently observed behavior?
Benchmark critique
No benchmark number is accepted as architectural evidence unless it says which layer it tests and what it misses: lifecycle, scope boundaries, authority, context cost, and governance.
Related systems
Related tools should be connected by evidence-backed edges: competes with, integrates with, implements concept, evaluated by, or has governance gap.
Update history
Provisional profile created. Stale-review detection, source snapshots, and changelog watching are required before this becomes a durable review.