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 baphuongna/pi-crew --skill secure-agent-orchestration-reviewgit clone --depth 1 https://github.com/baphuongna/pi-crewWrote 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/baphuongna/pi-crew/secure-agent-orchestration-review)<a href="https://agentmods.dev/skills/baphuongna/pi-crew/secure-agent-orchestration-review"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/secure-agent-orchestration-review/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/baphuongna/pi-crew/secure-agent-orchestration-review"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/secure-agent-orchestration-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 71 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00034 | $0.00680 |
| Opus 5 | $0.00017 | $0.00340 |
| Sonnet 5 | $0.00007 | $0.00136 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
secure-agent-orchestration-review 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 11d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
secure-agent-orchestration-review
Core principle: every delegated worker crosses trust boundaries. Safe orchestration requires contained paths, explicit ownership, scoped tools, non-invasive defaults, and prompt-injection resistance.
Distilled from detailed reads of security notice, insecure-defaults, sharp-edges, differential-review, guardrail, and skill quality patterns.
Trust Boundaries
Review:
- parent session ↔ child Pi worker;
- user prompt ↔ generated task packet;
- project skills ↔ package skills;
- global config ↔ project config;
- artifacts/logs ↔ future prompts/UI;
- mailbox/respond/steer/cancel ↔ session ownership;
- external skills/docs ↔ prompt injection/tool poisoning;
- runtime env/CLI args ↔ provider/model behavior.
Must-Check Findings
- Unsafe defaults: scaffold mode unexpectedly enabled, dangerous limits, missing depth guards, overbroad tools.
- Path containment: cwd override escape, symlink traversal, unsafe skill names, absolute path leakage.
- Prompt injection: untrusted output treated as instruction, skill metadata overtrusted, missing precedence text.
- Secrets: env/config/log/artifact/diagnostic leakage.
- Destructive commands: delete/prune/reset/force push without explicit confirmation.
- Ownership races: authorization checked outside lock, stale task/manifest written after re-read.
- Supply chain: external skill content imported without review, unknown tool requirements, hidden commands.
Secure Defaults for pi-crew
- Real execution should be explicit and disable-able, but generated config must not accidentally block normal workflows.
- Project overrides should be contained to the project root.
- Missing/invalid config should fall back safely.
- Skills should be loaded by safe name and source-labeled without absolute path disclosure.
- Worker prompts should state instruction precedence and treat artifacts as data.
Enforcement — Secure Agent Orchestration Review Gate
Before reporting security findings, verify:
- All trust boundaries examined (parent↔child, user↔task packet, project↔package skills, etc.)
- Must-check findings covered: unsafe defaults, path containment, prompt injection, secrets, destructive commands, ownership races, supply chain
- Finding format complete: severity, path/symbol, scenario, fix, verification
- Must-fix security issues separated from hardening suggestions
- Verification commands provided for each finding
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.
- 11d ago First seen · 74 lines · 34 tokens per session scan A fd2cc38fc773
secure-agent-orchestration-review is a skill published in the GitHub repository baphuongna/pi-crew (52 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 680 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 2026-08-30.
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