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eval-set

Build and run a project-specific retrieval eval so changes to your rules or base prompt are scored, not eyeballed.

Skill by fullymiddleaged

IndexedMIT★ 5
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/fullymiddleaged-eval-set

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About

Build and run a project-specific retrieval eval so changes to your rules or base prompt are scored, not eyeballed. Mirrors tests/ground_truth.json + `clawness eval`: you write prompt→expected-rule cases, then measure MRR@k and hit-rate before and after an edit. Run it after trimming a base prompt into ranked retrieval (see openclaw-audit / claude-md), or whenever you change rules and want proof retrieval still surfaces what matters.

Use cases: security, writing, agent-building

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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/eval-set

What's inside

Skill name
eval-set
Description
Build and run a project-specific retrieval eval so changes to your rules or base prompt are scored, not eyeballed. Mirrors tests/ground_truth.json + `clawness eval`: you write prompt→expected-rule cases, then measure MRR@k and hit-rate before and after an edit. Run it after trimming a base prompt into ranked retrieval (see openclaw-audit / claude-md), or whenever you change rules and want proof retrieval still surfaces what matters.
License
MIT
Instructions
122 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • cases.template.json

SKILL.md (first lines)

# Score your retrieval, don't eyeball it

When you move guidance out of an always-loaded base prompt (a bloated `CLAUDE.md`, an
OpenClaw `SOUL.md`/`AGENTS.md`) into Clawness's ranked retrieval, you trade a guarantee
for a probability: the content used to be present on *every* turn; now it surfaces only
when the prompt is relevant enough to rank it. That trade is usually right — it is the
whole point of `/clawness:claude-md` and `/clawness:openclaw-audit` — but it is only safe
if you can *check* that the content still surfaces for the prompts that need it.

This skill builds that check. It is the same machinery Clawness gates its own corpus with:
a labelled set of `prompt → expected rule ID(s)` cases, scored by MRR@k and hit-rate via
`clawness eval`. The output is a number that moves when retrieval regresses, so a rule edit
that quietly stops surfacing shows up instead of hiding until someone hits it in anger.

This is harness-agnostic — it evaluates Clawness retrieval, which is identical under Claude
Code and under the OpenClaw adapter. Nothing here touches OpenClaw's own prompt.

## When to run it

- **After trimming a base prompt** into `.clawness/rules/` — write a case for each thing
  the moved content used to guarantee, then confirm hit-rate is 1.0 before you delete the
  original. This is the verification step `openclaw-audit`/`claude-md` point at.
- **After editing or adding rules** — re-run to confirm you didn't push an existing rule
  out of the top-k for prompts that depend on it.
- **As a CI gate**, once the set is stable — the same `--floor-mrr`/`--floor-hit` floors
  Clawness uses on its own eval.

## Steps

### 1. Create the case file

Author `.clawness/eval/cases.json` in the shape below (a filled-in copy of this skill's
`cases.template.json`). Write it directly — the plugin root isn't reachable from skill
Bash, so don't try to `cp` the template from the plugin dir.

The shape (identical to `tests/ground_truth.json`):

```json
{
  "queries": [
    { "q": "how should I handle errors in our service layer", "expect": ["SVC-ERR-001"] }
  ]
}
```

- `q` — a prompt someone on this project would **actually type**. Write real phrasings,
  not the rule's own title; retrieval is lexical + concept-expansion, so the words matter.
- `expect` — the ranked rule ID(s) that should appear in the top-k. Any one of them
  counts as a hit, so list alternatives when more than one rule legitimately answers.
- `expect` targets **ranked** rules only. Mandatory rules (`_mandatory/`) are injected
  every turn and are not scored — don't put them here.

> Files under `.clawness/` are gitignored by Clawness's default allowlist. If you want the
> eval set committed and shared, add `!.clawness/eval/` to `.gitignore`.

### 2. Write good cases

- **One case per thing you care about surfacing.** If you moved five conventions out of a
  base prompt, that is at least five cases.
- **Phrase from the asker's side.** "make focus states visible for keyboard nav" beats
  "accessibility rule for focus" — the first is what a developer types.
- **Add near-miss cases too.** A prompt that should *not* pull a rule is worth a case with
  the correct rule expected, so a change that over-broadens a rule shows as a new miss
  elsewhere.
- **Keep the set stable.** Its value is as a fixed baseline; churning the cases every edit
  defeats the point. Grow it deliberately when you add a rule area.

### 3. Run it

The `clawness` CLI ships with the plugin but isn't on PATH; use the bundled
launcher, falling back to the bootstrap's wrapper on older Claude Code:

```bash
CLAW="${CLAUDE_PLUGIN_ROOT}/scripts/clawness-cli.sh"
[ -f "$CLAW" ] || CLAW="${CLAUDE_CONFIG_DIR:-$HOME/.claude}/clawness/clawness-cli.sh"
bash "$CLAW" eval --data .clawness/eval/cases.json
```

(Editable/manual installs may use `python -m clawness.cli eval --data ...`.)

It prints MRR@k, hit-rate, and every miss with what was expected versus what actually
ranked — which tells you exactly which case to fix and whether the fault is the rule's
`tags`/`triggers` or the case's phrasing.

### 4. Interpret and act on misses

For each miss (`expected [X]; got [...]`):

- If the right rule is missing from the list entirely, its `tags`/`triggers` don't carry
  the words the prompt uses — widen them (or the concept groups) rather than the case.
- If the right rule is present but below the cutoff, something else is out-ranking it;
  check whether a newly-added rule overlaps (`clawness audit-rules --overlap`).
- If the *case* is unrealistic (nobody would phrase it that way), fix the case, not the
  corpus.

Never "fix" a miss by deleting the case. A case you can't satisfy is telling you the
content you trimmed does *not* reliably surface — put it back in the base prompt and mark
it STAY.

### 5. Gate it (optional)

Once the set is stable and green, wire floors into CI so a regression fails the build:

```bash
bash "$CLAW" eval --data .clawness/eval/cases.json --floor-mrr 0.85 --floor-hit 0.95
```

Pick floors from your *current* passing numbers, not aspirational ones — a floor above
where you are just fails every build. `eval` exits non-zero when a floor is breached, so
it drops into a CI step directly.

## Don't

- Don't score mandatory rules — they're always injected; measuring them is noise.
- Don't chase MRR by rewording cases to match rule titles. The cases must stay realistic
  or the number stops meaning "will this surface for a real prompt".
- Don't set floors you don't currently meet.
- Don't treat a green eval as proof a base-prompt trim was safe on its own — it proves the
  *listed* prompts surface the content. Coverage is only as good as your cases; write one

From fullymiddleaged/Clawness, MIT.

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Last commit (this folder)
Oct 4, 2026 (24 days ago)
Last release
Oct 4, 2026 (24 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

eval-set skill. Agent Mart. https://agentmart.dev/skills/fullymiddleaged-eval-set (last updated 2026-10-24)