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About
Use cases: productivity, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/evaluate
Tools it pre-approves 5
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
ReadGrepGlobBashAgent
What's inside
- Skill name
evaluate- Description
- 0-arg eval extension. Replays transcripts and consumes workflow evidence against registered rubrics, preserving legacy Agent Behavior D1–D7 and reporting five harness-effectiveness components plus the nested measurement-integrity submetric (issue
- License
- MIT
- Allowed tools
- Read, Grep, Glob, Bash, Agent
- Instructions
- 120 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves any shell command
Files (1)
- SKILL.md
SKILL.md (first lines)
> [<- Skills index](../../README.md)
# /dev-kit:evaluate — Eval extension (Phase 3)
Runs the existing eval dimensions and adds workflow-evidence-based
harness-effectiveness reporting. Backward-compatible: the existing review,
security, plan, harness-quality, os-quality, and D1–D7 contracts remain
unchanged. The effectiveness result is gated on structured evidence (via
`lib.eval_runner.RubricRegistry`), which is the deterministic enforcement hook
that prevents the LLM judge from scoring against an unknown rubric.
The `alpha: enforcement` declaration is required by Iron Law L6 — the
deterministic registry lookup is the part the model cannot self-impose.
## Modes
- `/dev-kit:evaluate` (default): run the existing per-dim eval, legacy D1–D7,
and the five harness-effectiveness components in one report. The
`measurement_integrity` component now carries a nested `stability`
submetric (issue #663) covering agent / model / provider swap
behaviour; missing evidence there is reported as `INSUFFICIENT_EVIDENCE`,
not `0.0`. `build_report` returns `schema_version: 2` to advertise
the new submetric — consumers that ignore unknown versions continue
to work unchanged.
- `/dev-kit:evaluate --harness-quality`: register `harness-quality` rubric +
judge prompt with `RubricRegistry`, then run per-dim eval against the
`harness` DIM_AXES tuple.
- `/dev-kit:evaluate --os-quality`: register `os-quality` rubric + judge
prompt, then run per-dim eval against the `os` DIM_AXES tuple.
- `/dev-kit:evaluate --harness-quality --os-quality`: both, in sequence.
- `/dev-kit:evaluate --case <case_id>`: restrict to a single case fixture.
- `/dev-kit:evaluate --dry-run`: skip the LLM judge; mock each case at
7.0 / DRIFT_WARNING (same shape as the legacy `--dry-run`).
The effectiveness components are not enabled by a new option. They consume
workflow evidence already produced by TraceLog, repair-coordinator events,
guard/verification producers, and existing eval artifacts. Missing evidence is
reported as `INSUFFICIENT_EVIDENCE`; it is never inferred from a transcript or
converted to a passing/zero score.
## Rubric registry (deterministic enforcement)
`lib/eval_runner.RubricRegistry` is the registry this skill writes to. The
call path is:
```
--harness-quality -->
RubricRegistry.register(
name="harness-quality",
rubric_yaml_path="eval/rubrics/harness-quality.yaml",
judge_prompt_path="eval/prompts/judge-harness-quality.md",
)
judge against DIM_AXES["harness"]
--os-quality -->
RubricRegistry.register(
name="os-quality",
rubric_yaml_path="eval/rubrics/os-quality.yaml",
judge_prompt_path="eval/prompts/judge-os-quality.md",
)
judge against DIM_AXES["os"]
```
If the flag is passed but the corresponding YAML or judge prompt is missing
on disk, the skill must exit non-zero with a clear message — never silently
score against an unknown rubric.
## Cross-validate (3-judge variance gate)
Each per-case eval can fan out to three judges. When the population variance
of their per-axis means exceeds `0.5`, the result sets
`escalate: true` via `lib/analysis_core/cross_validate.cross_validate_scores`.
A report with any `escalate: true` block requires human review before being
treated as a clean PASS.
The threshold (`ESCALATE_VARIANCE_THRESHOLD = 0.5`) lives in
`lib/analysis_core/cross_validate.py` — single source of truth.
## Verdict (per-case axis mean)
Same thresholds as the legacy eval:
- **OK** at >= 8.0
- **DRIFT_WARNING** 5.0-7.9
- **ROT** < 5.0
A run that contains any `escalate: true` block is reported with verdict
`ESCALATED` regardless of axis mean — escalation beats the mean, because
"the judges disagree" is itself a defect signal.
## Output
- Per-dim markdown report written to `.dev-kit/eval-report.md` (legacy shape).
- Per-dim JSON result block (legacy shape) on stdout, plus an
`escalations` list when cross-validate disagrees.
- Exit 0 if all cases OK (or DRIFT_WARNING + no escalations). Exit 1
on any ROT or escalation.
## Backward-compat
- `--harness-quality` and `--os-quality` are NEW flags. Without them,
the skill behaves exactly like the pre-Phase-3 eval.
- `RubricRegistry` is class-level and starts empty. Existing call
sites that do not import or call `register()` are unaffected.
- The harness-effectiveness reducer gains a nested `stability` submetric
under `components.measurement_integrity.submetrics.stability` (issue
#663). `build_report` returns `schema_version: 2`. The 4-component
`overall_score` contract is preserved — `COMPONENT_WEIGHTS` still
sums to 1.0 and no top-level weight is added for stability. Missing
stability evidence surfaces as `status: INSUFFICIENT_EVIDENCE` with
`score: null` (never `0.0`). `INSUFFICIENT_EVIDENCE` is exported
from `lib.harness_effectiveness` as a sentinel string constant.
## Next step
- After a passing harness-quality + os-quality run: hand off to
`/dev-kit:ship` if this is a release branch, or `/dev-kit:status`
to confirm the eval cycle is green.
- After a failed run: triage via `/dev-kit:babysit-pr` if the failure
is on a PR, or re-run `/dev-kit:evaluate` after fixing the failing case.From sh-ai-x/dev-harness-kit, MIT.
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SkillAFreshness: A★ 1Claude Code +9 - 0.584score
babysit-pr-local
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0-arg local-mode PR babysitter.
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harness-mode
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gate-select
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bootstrap
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SkillAFreshness: A★ 1Claude Code +9 - 0.581score
guard-mode
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Session-scoped on/off toggle for the tdd-guard, worktree-guard, and git-guard hard-block hooks.
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babysit-pr
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0-arg restart-safe PR check, diagnose, fix, and hand-off loop.
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build
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0-arg.
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codex-cache-update
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Refresh the dev-kit Codex marketplace checkout and synchronize the versioned plugin cache.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
bump
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Explicit version bump of `.claude-plugin/plugin.json` + push of `chore/bump-vX.Y.Z`.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
evidence-plan
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Idea → cited research → HTML proposal (human confirms) → /dev-kit:plan hand-off.
SkillBFreshness: B★ 1Claude Code - 0.544score
ci-update
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Detect + selectively apply drift between installed CI templates and current dev-kit source.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 2
- Open issues
- 8
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/sh-ai-x/dev-harness-kit
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from sh-ai-x
- 0.587score
harness-effectiveness
sh-ai-x
0-arg harness-effectiveness report.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
harness-mode
sh-ai-x
Session-scoped local-hook mode picker — fast (all optional local hooks off), full (default, all on), or custom (interactive per-local-hook picker via…
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
babysit-pr-local
sh-ai-x
0-arg local-mode PR babysitter.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
gate-select
sh-ai-x
Unified 3-dimension picker for project / session / AI-judge gates.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
guard-mode
sh-ai-x
Session-scoped on/off toggle for the tdd-guard, worktree-guard, and git-guard hard-block hooks.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
bootstrap
sh-ai-x
0-arg setup for CLAUDE.md, AGENTS.md, hooks, and optional CI.
SkillAFreshness: A★ 1Claude Code +9
Done for you
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Cite this page
evaluate skill. Agent Mart. https://agentmart.dev/skills/sh-ai-x-evaluate (last updated 2026-10-24)