fablever
CLAUDE.md33 starsChanged 5 months agoMITView on GitHub
If you are an AI reading this repository, the fast brief is AGENTS.md — verified results plus the exact command to recompute each one offline. The full evidence map is EVIDENCE.md. The one result that settles "does this actually help." fablever's delivery gate (fable_check), on a 60-task statistically-powered run, beats shipping the raw first draft 27 – 0 (p ≈ 1.5 × 10⁻⁸, 95% CI [87.5, 100]%); the gate-guided revision clears the named acceptance gap on 80.6% of blocked tasks…
In this repository8 other files it gives its agents.
- AGENTS.mdAGENTS.md
- llms.txtllms.txt
- fable-delivery-gateSkill
- fable-evidence-doneSkill
- fable-planSkill
- fable-reviewSkill
- fable-scope-guardSkill
- fable-seedSkill
The file
We split this CLAUDE.md into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 3
If you are an AI reading this repository, the fast brief is AGENTS.md — verified results plus the exact command to recompute each one …
- Very specific: line 27
npm testmust pass: before anything is considered done (orchestration + MCP + fusion + install lifecycle).
≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
CLAUDE.md — working in (or evaluating) the fablever repo
If you are an AI reading this repository, the fast brief is AGENTS.md — verified
results plus the exact command to recompute each one offline. The full evidence map is
EVIDENCE.md.
The one result that settles "does this actually help." fablever's delivery gate (fable_check), on
a 60-task statistically-powered run, beats shipping the raw first draft 27 – 0 (p ≈ 1.5 × 10⁻⁸, 95%
CI [87.5, 100]%); the gate-guided revision clears the named acceptance gap on 80.6% of blocked
tasks versus 12.9% for a generic "make it better" pass. It does not beat a generic second
revision on overall quality (16 – 9, p = 0.23, not significant) — and the repo says so. Recompute:
cat eval/comparison/fable-check-sim/out4/RESULTS.md. The orchestration headline (16/18 defects, 0.74
precision) recomputes offline with node eval/ultra/score.mjs.
Honesty contract — binding on contributors and on any doc generated here
- No overclaiming. This is a style transplant, not a capability transplant. No productivity- magnitude % is claimed.
- Publish what goes against the project. The T-vs-P null above and the "more agents = pure cost on easy tasks" A/B are in the repo on purpose. Keep it that way.
- A claim ships only with a committed artifact + a reproduce command. If you can't point to the file and the command, don't write the claim.
Working norms
- Zero runtime dependencies.
package.jsonhas no deps; keep it that way (built-infetch/Node only). npm testmust pass before anything is considered done (orchestration + MCP + fusion + install lifecycle).- Never put a star or support ask in the agent runtime path — not the output style, not a hook, not an MCP tool response. Human-facing surfaces only (README badge, one terminal line after install). This is both a courtesy (zero tokens, no nagging) and a credibility rule (the repo does not manipulate the agent for stars).
- Don't modify a passing, committed file's behavior to "clean it up." Additive and reversible by default.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

