Borrowing it
Nothing to install: this file belongs to hoophq/hoop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hoophq/hoop/main/.claude/skills/evidence/SKILL.mdgit clone --depth 1 https://github.com/hoophq/hoopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hoophq/hoop/evidence)<a href="https://agentmods.dev/skills/hoophq/hoop/evidence"><img src="https://agentmods.dev/badge/skills/hoophq/hoop/evidence/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hoophq/hoop/evidence"><img src="https://agentmods.dev/badge/skills/hoophq/hoop/evidence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.02722 |
| Opus 5.5 | $0.00030 | $0.01089 |
| Sonnet 5.5 | $0.00015 | $0.00544 |
| Haiku 4.5 | $0.00007 | $0.00272 |
Grade A, and why
evidence scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| "Does the sidecar get the same rules?" | `GET /api/sidecars/configuration` | `curl \| jq` → PNG | How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence for a ticket
Evidence is what convinces a person in two minutes that the change works and breaks nothing. A reader must be able to COMPARE: every image puts "before" and "after" side by side, with a label on each panel. Model: "Testing" in PR #1937.
Deliverable, and nothing else, in ~/evidencias/<TICKET-ID>/:
EVIDENCE.md
1-<question>.png one comparison image per question, 2 to 4 in total
2-<question>.png
When the change has a flow, the comparison is a video of it instead: a UI
flow (model: ENG-596), or a terminal flow with each step explained on screen.
<flow>.gif for the PR and <flow>.mp4 for Linear, 1 or 2 flows. A PNG stays
for a single state: one API response, one log line.
Everything else (raw captures, logs, snapshots, scripts, test output) goes to
~/evidencias/.archive/<TICKET-ID>/. Never inside the ticket folder.
1. Plan the captures (before you run anything)
For each Definition of done item, write one line:
| Question a reader asks | Surface a person meets | Capture |
|---|---|---|
| "Does the sidecar get the same rules?" | GET /api/sidecars/configuration |
curl | jq → PNG |
| "Does the admin screen change?" | rule edit page | browser screenshot |
| "Is the page fast, and does it show X?" | the page, used end to end | recorded flow → side-by-side GIF/MP4 |
| "Does the CLI tell the user why?" | hoop exec, then the session API |
VHS tape → side-by-side GIF/MP4 |
Surfaces, best first: the UI; an API response; a sidecar, gateway or agent log
line; CLI output. Never an internal DB snapshot or go test output: a test is
proof for CI, not for a reader.
When the UI changes, the surface is the flow, recorded: a still hides what a click does. When the ticket adds a view, show its layout to the human as soon as it renders, before building its backend: the first look can remove it.
Add a third column, DURING DEPLOY (origin/main code reading the database
the branch migrated), when the ticket has a migration, a wire/packet change, or
a sidecar config change. Gateways auto-deploy and roll; that is where things
break.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- compare.sh 2.4 KB runs code
- compose-video.sh 1.6 KB runs code
- examples/access-control.flow.mjs 2.4 KB runs code
- examples/reject-live/cors_files.py 494 B runs code
- examples/reject-live/README.md 938 B
- examples/reject-live/record-side.sh 1.0 KB runs code
- examples/reject-live/reject-live.flow.mjs 2.0 KB runs code
- examples/terminal.tape 948 B
- label.sh 1.8 KB runs code
- LEARNINGS.md 4.4 KB
- publish.sh 2.2 KB runs code
- rec.mjs 8.9 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +29 lines · +2 tokens per session 44885a438499
- 7d ago Changed · +5 lines ff1847030fcd
- 12d ago Changed · +48 lines · +10 tokens per session 5e2f986588cc
- 13d ago First seen · 128 lines · 63 tokens per session scan A 0cf8c988b1fe
evidence is a skill published in the GitHub repository hoophq/hoop (837 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 2,722 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-14.
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commit
Prepare and create git commits for dynobox. Use this skill whenever the user asks to commit, create a commit, suggest a commit message, stage changes, or prepare changes for review. Also use it when the user asks whether the changelog should be updated before committing.
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Review code changes, pull requests, patches, or a scoped code area for actionable correctness, security, compatibility, and test risks with file and line evidence. Use for review or audit requests; do not use for general proofreading, feature implementation, or debugging a reported failure when the user wants a fix.
debug
Diagnose a concrete failure, regression, crash, hang, flaky test, or incorrect runtime behavior by reproducing it, testing hypotheses, and identifying the evidence-backed root cause. Use when symptoms or failing output exist; do not use for feature implementation without a failure, general code review, or a conceptual…
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Test coverage quality analysis — behavioral coverage, critical gap identification, test resilience evaluation.