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 PracticalSwan/agent-skills --skill agent-skillguardgit clone --depth 1 https://github.com/PracticalSwan/agent-skillsWrote 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/practicalswan/agent-skills/agent-skillguard)<a href="https://agentmods.dev/skills/practicalswan/agent-skills/agent-skillguard"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/agent-skillguard/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/practicalswan/agent-skills/agent-skillguard"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/agent-skillguard.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 | $0.00055 | $0.01045 |
| Opus 5 | $0.00028 | $0.00522 |
| Sonnet 5 | $0.00011 | $0.00209 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
agent-skillguard 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 4d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Risk Check
Use this skill when the user asks whether an agent skill or plugin should be trusted, installed, reviewed, or admitted.
Non-negotiable boundary
Scanning is read-only. Never execute, source, import, install, or enable the target artifact during review. A clean report is not proof that an artifact is safe, and a finding is not proof of malicious intent.
Workflow
- Identify the exact local target and its provenance.
- Run
python <catalog-root>/agent-skillguard/scripts/skillguard.py scan <path> --format markdownbefore any installation step. Use the absolute catalog path when the host does not expand<catalog-root>. - Review every active finding at its exact file and line.
- Separate confirmed behavior, ambiguous behavior, and false positives.
- If a false positive is accepted, suppress only its exact fingerprint, rule ID, and rule version with a concrete reason.
- Re-run the scan and report both active and suppressed counts.
- Stop before installation or permission grants unless the user separately authorized them.
- When evaluating the scanner itself, scan
agent-skillguard/fixtures/positive(expected review findings) andagent-skillguard/fixtures/negative(expected clean result) with the bundled script, and inspectrules/non-coverage.json. The installed plugin package does not ship the upstreamtools/verify_rule_corpus.pyhelper, so do not claim that helper ran; the two fixture scans are the supported local smoke test.
Packaging Notes
This catalog copy is intentionally self-contained: it includes the scanner, rule JSON, schemas, and public fixtures, but not the plugin's host metadata, examples, or large assets. The scanner resolves its rules relative to this skill directory, so invoke it through the bundled Python script rather than assuming a globally installed skillguard command.
Exit codes
0: no active findings at or above the selected severity.1: at least one active finding requires review.2: the scan could not be completed reliably.
What ships with it
19 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.
- CHANGELOG.md 1.1 KB
- fixtures/fixture-manifest.json 2.0 KB
- fixtures/negative/hierarchy.md 79 B
- fixtures/negative/least-privilege.json 40 B
- fixtures/negative/narrow-delete.ps1 49 B runs code
- fixtures/negative/reviewed-download.md 123 B
- fixtures/positive/sg001.md 81 B
- fixtures/positive/sg002.sh 9 B runs code
- fixtures/positive/sg003.json 27 B
- fixtures/positive/sg004.md 45 B
- fixtures/positive/sg005.ps1 52 B runs code
- fixtures/positive/sg006.ps1 61 B runs code
- fixtures/positive/sg007.sh 56 B runs code
- fixtures/positive/sg008.md 66 B
- report.schema.json 978 B
- rules/default-rules.json 4.8 KB
- rules/non-coverage.json 848 B
- scripts/skillguard.py 20 KB runs code
- suppressions.schema.json 921 B
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.
- 4d ago Changed 44a58ff54666
- 6d ago First seen · 86 lines · 55 tokens per session scan A f37391097023
agent-skillguard is a skill published in the GitHub repository PracticalSwan/agent-skills (14 stars, last pushed 4d ago), licensed MIT. It adds 55 tokens to every session and 1,045 once invoked, about $0.0003 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 2026-09-06.
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