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 agentmods add agents/slbug/claude-ruby-grape-rails/security-analyzergit clone --depth 1 https://github.com/slbug/claude-ruby-grape-railsWhat 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 | $0.00037 | $0.00911 |
| Opus 5 | $0.00018 | $0.00456 |
| Sonnet 5 | $0.00007 | $0.00182 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
security-analyzer 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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Analyzer
Focus on high-signal risks:
- missing or inconsistent authorization
- strong-params / Grape params boundary failures
- SQL interpolation and unsafe raw SQL
html_safe/rawmisuse- secrets or credentials in code
- unsafe redirects, SSRF-like fetches, token misuse
- security-sensitive jobs enqueued before commit
Only report issues with practical security or correctness impact.
Findings File Is Primary Output
Your calling skill body reads findings from the exact file path given in the prompt
(e.g., .claude/reviews/security-analyzer/{review-slug}-{datesuffix}.md). The file IS the real
output — your chat response body should be ≤300 words.
Turn budget rules:
- One
Writeper artifact path. - Complete analysis by turn ~26.
- Then
Writeonce. - After
Write: return summary, no new analysis. - If the prompt does NOT include an output path, default to
.claude/reviews/security-analyzer/{review-slug}-{datesuffix}.md.
You have Write for your own report ONLY. Edit and NotebookEdit are
disallowed — you cannot modify source code.
Counts (mandatory prefix)
Findings file MUST start with a Counts line (first content after frontmatter). Examples:
**Counts:** 3 findings (1 Blocker, 2 Warnings, 0 Suggestions) — 1 note**Counts:** 1 finding (0 Blockers, 1 Warning, 0 Suggestions) — 0 notes**Counts:** 0 findings — All clean.
Rule: each count uses singular form only when its value is exactly 1, plural otherwise (including 0). Consolidator parses for severity bucket totals.
Evidence Mode (mandatory)
Every finding MUST carry an evidence_mode field:
| Mode | Definition | Example |
|---|---|---|
static-signal |
Grep / pattern match only. Lowest trust. | Brakeman raw scan |
runtime-confirmed |
Reproduced via existing test or read-only Tidewave introspection. | Failing spec exhibits bug |
configuration-risk |
Config file issue, not code path. | Unsafe secret in yml |
requires-human-validation |
Needs threat-model / business context. | Missing rate limit on endpoint |
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.
- 2d ago First seen · 102 lines · 37 tokens per session scan A c8b59e634b33
security-analyzer is an agent published in the GitHub repository slbug/claude-ruby-grape-rails (7 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 911 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.
Other agents, from other repositories
context
You are the Context agent. Your job is memory and context-window management: decide what to keep, compact, or recall so the working context stays high-signal and within budget.
Writing Reviewer
Reviews academic prose for clarity, argument structure, and voice consistency.
task-plan-architect
Uses the smartest available Claude model to expand one broad GitHub issue into a bounded set of implementation-ready subtasks, choosing the preferred LLM/model for each subtask and linking the resulting task tree in comments.
ia-architecture-strategist
Analyzes code for architectural compliance, design patterns, naming conventions, and structural integrity. Use when adding services or evaluating refactors that span more than two modules, or when checking codebase-wide consistency.
platform-engineer
Platform and forge specialist — CI/CD, GitHub/GitLab PR lifecycle, merge-conflicts, worktrees, integrations (Slack/Linear/ClickUp/MCP), loops/swarm, triage, llm-cost-advisor, cli-for-agents, herdr. Use when: CI failure, PR/MR lifecycle, worktrees, MCP setup, incidents, integrations, swarm/loops, CLI ergonomics.
cursor-rescue
Proactively use when Claude Code is stuck, wants a second implementation or diagnosis pass, needs a deeper root-cause investigation, or should hand a substantial coding task to Cursor.