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 BlackPearl-AI/BlackPearl-CodingAgent --skill agency-ai-generated-code-security-auditorgit clone --depth 1 https://github.com/BlackPearl-AI/BlackPearl-CodingAgentWrote 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/blackpearl-ai/blackpearl-codingagent/agency-ai-generated-code-security-auditor)<a href="https://agentmods.dev/skills/blackpearl-ai/blackpearl-codingagent/agency-ai-generated-code-security-auditor"><img src="https://agentmods.dev/badge/skills/blackpearl-ai/blackpearl-codingagent/agency-ai-generated-code-security-auditor/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/blackpearl-ai/blackpearl-codingagent/agency-ai-generated-code-security-auditor"><img src="https://agentmods.dev/badge/skills/blackpearl-ai/blackpearl-codingagent/agency-ai-generated-code-security-auditor.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 | $0.00061 | $0.03831 |
| Opus 5 | $0.00030 | $0.01916 |
| Sonnet 5 | $0.00012 | $0.00766 |
| Haiku 4.5 | $0.00006 | $0.00383 |
Grade A, and why
agency-ai-generated-code-security-auditor 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 10d 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.
Strips warnings and disclaimerslowAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
- **Personality**: Calm, skeptical, and specific. You do not moralize about using AI to write code — you use it too. You assume good intent and bad defaults. You never say "this is insecure" without showing the exact lin Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 10d ago First seen · 204 lines · 61 tokens per session scan A fbad0034dc39
agency-ai-generated-code-security-auditor is a skill published in the GitHub repository BlackPearl-AI/BlackPearl-CodingAgent (7 stars, last pushed 10d ago), with no licence file. It adds 61 tokens to every session and 3,831 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
skills-constitution
A set of rules that makes an agent check its memory and available skills before handling professional tasks such as coding, file work, data analysis, or deployment.
doubt-driven-review
In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.
review-code
Review a code change well — engine-agnostic critical review discipline for an inline dev loop. Defines what to look for (design→correctness→complexity→tests→naming→security), a severity taxonomy, and a review→fix→re-review loop with a hard stop. Use on "review this code", "review my diff", "is this change good"…
code-review
AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security). Also drives the development inner loop: review uncommitted work, fix, re-review before commit.
code-quality
Drive static-analysis code quality in pi-agent-dashboard with Biome (analyze → fix → test), in changed-files or whole-repo mode. Use when asked to "improve code quality", "lint and fix", "clean up warnings", "fix Biome issues", "run static analysis", or when setting a code-quality goal. Skip for one-line edits.