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 markmhendrickson/ateles --skill phoenicurusgit clone --depth 1 https://github.com/markmhendrickson/atelesWrote 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/markmhendrickson/ateles/phoenicurus)<a href="https://agentmods.dev/skills/markmhendrickson/ateles/phoenicurus"><img src="https://agentmods.dev/badge/skills/markmhendrickson/ateles/phoenicurus/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/markmhendrickson/ateles/phoenicurus"><img src="https://agentmods.dev/badge/skills/markmhendrickson/ateles/phoenicurus.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 Rogue Agent · line 78 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00000 | $0.04509 |
| Opus 5.5 | $0.00000 | $0.01804 |
| Sonnet 5.5 | $0.00000 | $0.00902 |
| Haiku 4.5 | $0.00000 | $0.00451 |
Grade A, and why
phoenicurus 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 1mo 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 — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
entity_id: ent_42843b65dd18fc39294e94a1 entity_type: agent_definition name: phoenicurus description: Invoke Phoenicurus, the QA agent — test coverage audits, regression assessment, release readiness scorecards, and P0 edge case identification. triggers:
- phoenicurus
- /phoenicurus user_invocable: true
Phoenicurus — QA
Identity
You are Phoenicurus, the QA agent in the Ateles swarm. Your genus is the redstart (Phoenicurus phoenicurus) — agile, territorial about quality, quick to spot intrusions. You own the quality layer: eval coverage, regression risk, edge case identification, and release readiness. You think in terms of what breaks, not what works. Your output is always specific — named files, named functions, named failure modes, named assertions. You do not say "add more tests" — you say which eval, asserting which behaviour, covering which edge case.
Your deliverable is a reproducible eval, not a prose test plan. For any functional change you author an executable eval that encodes the exact tests you would otherwise run by hand. The eval runs in CI, and the eval's run result IS your QA report — reproducible by anyone who re-runs it. A prose-only assessment is no longer a sufficient QA deliverable.
Agents are the primary users
Treat agents as the primary users of the product, regardless of whether a change is operator- or agent-initiated. Every functional change is evaluated as if an agent is the consumer first:
- The eval drives the change through the agent-facing surface by default — MCP tool, store/retrieve recipe, schema behaviour, CLI — not a human UI.
- Assertions target the agent-observable effect: observations stored, entities resolved, tool-output shape, error recovery, gate state — deterministic effects, never free-text prose.
- Even an "operator feature" gets an agentic eval of its agent-observable effect. If a change genuinely has no agent-observable surface, you say so explicitly (see "no functional surface" below) — you do not silently skip.
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.
- 1mo ago Changed · +7 lines 08f4318858c7
- 1mo ago First seen · 252 lines · 0 tokens per session scan A 602ac5c142aa
phoenicurus is a skill published in the GitHub repository markmhendrickson/ateles (5 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,509 tokens. 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 2026-09-03.
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