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 Samurai-goose/SPECTER-The-Illusive-Security-Protocol --skill secure-code-reviewgit clone --depth 1 https://github.com/Samurai-goose/SPECTER-The-Illusive-Security-ProtocolWrote 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/samurai-goose/specter-the-illusive-security-protocol/secure-code-review)<a href="https://agentmods.dev/skills/samurai-goose/specter-the-illusive-security-protocol/secure-code-review"><img src="https://agentmods.dev/badge/skills/samurai-goose/specter-the-illusive-security-protocol/secure-code-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/samurai-goose/specter-the-illusive-security-protocol/secure-code-review"><img src="https://agentmods.dev/badge/skills/samurai-goose/specter-the-illusive-security-protocol/secure-code-review.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 | $0.00044 | $0.02146 |
| Opus 5 | $0.00022 | $0.01073 |
| Sonnet 5 | $0.00009 | $0.00429 |
| Haiku 4.5 | $0.00004 | $0.00215 |
Grade A, and why
secure-code-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 9d 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secure Code Review
Purpose
Perform systematic, source-level security analysis of application code. Identify injection vulnerabilities, authentication/authorization flaws, cryptographic weaknesses, unsafe data handling, business logic bugs, and insecure patterns. Produce actionable findings with exact file locations, code snippets, and remediation guidance.
Triggers
- User requests code review for security issues
- New code added to repository (PR review)
- Recon analysis identifies code-level investigation targets
- Bug bounty triage routes a finding for code-level analysis
- Dependency audit surfaces code-level usage of vulnerable library
Required Inputs
| Input | Description | Required |
|---|---|---|
governance_context |
Active engagement governance record | Yes |
target_files |
Files, directories, or patterns to review | Yes |
language |
Primary programming language(s) | Auto-detected |
framework |
Framework in use (Express, Django, Rails, etc.) | Auto-detected |
focus_areas |
Specific vulnerability classes to prioritize | Recommended |
context |
Business context: what the code does, data sensitivity | Recommended |
Workflow
-
Scope & Context — Identify language, framework, and application purpose. Understand data flows and trust boundaries.
-
Entrypoint Mapping — Find all external input sources:
- HTTP request handlers (routes, controllers)
- CLI argument parsers
- File readers / parsers
- Database query builders
- Message queue consumers
- WebSocket handlers
- Deserialization points
-
Taint Analysis — Trace data flow from each input source:
- Where does user input enter?
- What transformations are applied? (validation, sanitization, encoding)
- Where does it reach a sink? (SQL query, command execution, HTML output, file system, redirect)
- Are there gaps in the sanitization chain?
-
Vulnerability Pattern Scan — Check for each class:
Injection
- SQL injection: string concatenation in queries, missing parameterization
- Command injection: user input in
exec,system,spawn,popen - XSS: unescaped output in HTML,
innerHTML,dangerouslySetInnerHTML - Template injection: user input in template strings/engines
- Path traversal: user input in file paths without sanitization
- LDAP/XPath/NoSQL injection: unparameterized queries
- Header injection: user input in HTTP headers
- Log injection: unsanitized input in log statements
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.
- 9d ago First seen · 229 lines · 44 tokens per session scan A 148e5a436881
secure-code-review is a skill published in the GitHub repository Samurai-goose/SPECTER-The-Illusive-Security-Protocol (2 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 2,146 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.
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