Report how each arm reached the docs, and how often it got nothing - #64
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`report-results` now prints, per experiment, how many documentation calls reached a page, how many came back empty, and the tool mix behind both. The raw data was already captured per call; nothing new is collected. Recording rather than equalising, deliberately. A skill's job here is to point at the documentation rather than restate it, so an agent fetching a docs URL because a skill named it is the skill working — not a confound to design out. Equalising that would remove the mechanism along with the noise. Printing it per experiment rather than per arm changed the conclusion. Pooled, it reads as a skills effect: 296 calls in -no-skills against 83 in +skills, 58% empty against 37%. Split out, both Claude arms sit at 0% empty and every Codex arm is between 26% and 83% — Claude Code reaches docs with web_fetch, which returns a page, while Codex leans on web_search, which often returns none. A real skills effect survives inside each Codex pair and it is the smaller term. The aggregate hid that by pooling two agents with different habits, which is what #61 asserted and this corrects. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Nt2Zgjw7STjrnFXYKRRVAA
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Records the documentation-access gap from #61 rather than equalising it, per the decision that a skill pointing at the single source of truth is the skill working.
report-resultsgains a per-experiment breakdown: calls that reached a page, calls that came back empty, and the tool mix behind both. No new data is collected —buildDocsResultalready capturedsource,pagesandresultCharsper call. This just reads it.Printing it per experiment changed the conclusion
Pooled by arm, it reads as a skills effect: 296 calls in
-no-skillsagainst 83 in+skills, 58% empty against 37%. That is what #61 asserts. Split by experiment on the 25 August snapshot:Both Claude arms are at zero. Claude Code reaches documentation with
web_fetch, which returns a page; Codex leans onweb_search, which frequently returns none.A real skills effect does survive inside each Codex pair — 60% against 73%, and 26% against 83% — but it is the smaller term. The dominant variable is which agent CLI, and pooling two agents with different habits hid that.
That matters for the milestone-2 run: a skills delta computed across both agents will carry an agent-shaped artefact unless this is read per row.
Why record and not equalise
Equalising — telling both arms in the prompt that docs are fetchable over HTTP — would remove the mechanism along with the noise. If the skills are meant to point at the documentation rather than duplicate it, an agent fetching a docs URL because a skill named it is the thing we are trying to measure.
Recording keeps that visible and separates it from the part that genuinely is noise: an external search index returning nothing.
Verification
pnpm typecheckclean,pnpm -r testgreen (254 tests), output verified against the 25 August snapshot.🤖 Generated with Claude Code
https://claude.ai/code/session_01Nt2Zgjw7STjrnFXYKRRVAA