Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wyattowalsh/agents --skill add-badgesgit clone --depth 1 https://github.com/wyattowalsh/agentsWrote 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/wyattowalsh/agents/add-badges)<a href="https://agentmods.dev/skills/wyattowalsh/agents/add-badges"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/add-badges/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/wyattowalsh/agents/add-badges"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/add-badges.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 | $0.00040 | $0.03309 |
| Opus 5 | $0.00020 | $0.01655 |
| Sonnet 5 | $0.00008 | $0.00662 |
| Haiku 4.5 | $0.00004 | $0.00331 |
Grade A, and why
add-badges scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Badges
Generate and update README badge blocks without drifting into general README editing.
Dispatch
| $ARGUMENTS | Action |
|---|---|
| Empty | Show the empty/help gallery and ask for the target repo or README path |
| Flags or natural-language badge request | Run the full badge workflow: detect -> select -> present -> insert |
--dry-run with any request |
Run through preview only and stop before file edits |
| removal-only request | Skip detection, inspect the existing badge block, and present the reduced set |
Empty/Help Gallery
When $ARGUMENTS is empty, show the main usage shape plus examples:
/add-badges --profile active --dry-run/add-badges --include status,package --readme README.md/add-badges --replace --yes/add-badges remove social badges
State the main phases and the write boundary:
- Detect the repo and existing badge state
- Select badges and layout based on flags and detected signals
- Present the proposed block and diff indicators
- Insert only after approval, unless
--yeswas explicitly passed
Progressive Disclosure
- Keep
SKILL.mdfocused on routing, phase order, approval boundaries, and flag semantics. - Read
references/badge-catalog-core.mdon every run. - Read
references/badge-catalog-extended.mdonly when non-basic signals are detected. - Read
references/style-guide.mdonly when layout, format-specific syntax, or dark-mode output matters. - Use
scripts/detect.pyfor repository detection andscripts/validate-badges.pyonly after insertion when verification is requested.
Internal Phase 1 — Detect
Run the detection script via the Bash tool:
uv run python skills/add-badges/scripts/detect.py <path>
Parse the JSON output. The script detects: repo info, languages, package managers, frameworks, CI/CD, infrastructure, code quality, testing, docs, license, release, security, community, developer tooling, databases, monorepo signals, and existing badges.
If the script fails (uv unavailable, Python missing, script error, invalid JSON), fall back to manual detection:
- Glob for manifest files (pyproject.toml, package.json, go.mod, Cargo.toml, etc.)
- Read
.git/configor rungit remote get-url originfor owner/repo - Glob
.github/workflows/*.ymlfor CI badge candidates - Read LICENSE first line for SPDX type
- Check for Dockerfile, .pre-commit-config.yaml, codecov.yml, etc.
What ships with it
14 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.
- evals/evals.json 2.3 KB
- references/badge-catalog-core.md 11 KB
- references/badge-catalog-extended.md 16 KB
- references/style-guide.md 9.3 KB
- scripts/asset_toolkit/__init__.py 303 B runs code
- scripts/asset_toolkit/_shared.py 5.6 KB runs code
- scripts/asset_toolkit/common.py 3.0 KB runs code
- scripts/asset_toolkit/package.py 43 KB runs code
- scripts/asset_toolkit/validate_evals.py 11 KB runs code
- scripts/asset_toolkit/validate_hooks.py 13 KB runs code
- scripts/asset_toolkit/validate_skill.py 3.6 KB runs code
- scripts/check.py 2.2 KB runs code
- scripts/detect.py 43 KB runs code
- scripts/validate-badges.py 4.3 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.
- 9d ago First seen · 234 lines · 40 tokens per session scan A bad9503e307d
add-badges is a skill published in the GitHub repository wyattowalsh/agents (5 stars, last pushed 6d ago), licensed MIT. It adds 40 tokens to every session and 3,309 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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