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.
git clone --depth 1 https://github.com/ogrodev/fsocietyWrote 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/commands/ogrodev/fsociety/apiscan)<a href="https://agentmods.dev/commands/ogrodev/fsociety/apiscan"><img src="https://agentmods.dev/badge/commands/ogrodev/fsociety/apiscan/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/commands/ogrodev/fsociety/apiscan"><img src="https://agentmods.dev/badge/commands/ogrodev/fsociety/apiscan.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 | $0.00014 | $0.00556 |
| Opus 5.5 | $0.00006 | $0.00222 |
| Sonnet 5.5 | $0.00003 | $0.00111 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
apiscan 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 2mo 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Storage Policy: ALL output files MUST be saved in the project directory. NEVER write to
/tmp/or any system temporary directory.
API Security Audit
Target: $ARGUMENTS
Execute a comprehensive API security audit using Hexstrike MCP tools.
Step 1: Load Tools
Use ToolSearch to load:
comprehensive_api_audit— full API security auditapi_fuzzer— endpoint and parameter fuzzingjwt_analyzer— JWT token analysis and attack testinggraphql_scanner— GraphQL introspection and injection testingarjun_parameter_discovery— hidden parameter discoveryapi_schema_analyzer— OpenAPI/Swagger schema analysis
Step 2: Schema Discovery
Check for common API documentation endpoints:
/swagger.json,/openapi.json,/api-docs/graphqlwith introspection query- Run
api_schema_analyzerif a schema is found
Step 3: Comprehensive Audit
Run comprehensive_api_audit against the API base URL. This performs broad coverage testing including auth, injection, access control, and business logic.
Step 4: JWT Analysis
If JWT tokens are in scope, run jwt_analyzer to:
- Decode and inspect token claims
- Test algorithm confusion (alg:none, RS256→HS256)
- Check signature validation
- Test expiration enforcement
- Attempt key brute-forcing for HS256
Step 5: Parameter Discovery
Run arjun_parameter_discovery on key endpoints to find hidden/undocumented parameters that may bypass access controls or enable injection.
Step 6: Fuzzing
Run api_fuzzer on discovered endpoints with:
- Method fuzzing (GET/POST/PUT/DELETE/PATCH)
- Content-type confusion (JSON vs urlencoded vs XML)
- Parameter type confusion (string vs int vs bool vs array)
- Auth bypass headers (X-Forwarded-For, X-Original-URL)
Step 7: GraphQL (if applicable)
Run graphql_scanner for:
- Introspection enumeration
- Injection testing on fields
- Depth/complexity abuse
- Batch query attacks
Step 8: Results
Save findings to apiscan-{target}.md in the project directory, organized by:
- Authentication/Authorization issues
- Injection vulnerabilities
- IDOR / Access control failures
- Information disclosure
- Business logic flaws
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.
- 2mo ago First seen · 65 lines · 14 tokens per session scan A ad94d74e1538
apiscan is a command published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 556 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other commands, from other repositories
better-auth:add-plugin
Add a better-auth plugin to an existing project. Configures server and client plugins with proper imports.
better-auth:setup
Interactive setup wizard for better-auth authentication. Guides through database, framework, OAuth providers, and plugin configuration.
symfony-cache
Implement caching strategies using Symfony Cache component.
pentest-attacks
Define the attack profile for an engagement — select which attack categories and skills to use. Saves to .pentest-attacks.json. If run before /pentest:pentest, the orchestrator will respect the selection. If run standalone, does not launch a pentest.
setup
Interactive auth setup wizard. Choose provider, configure OAuth, email, generate schema, create UI components — all in one command.
ds-package
Package a model as a servable unit and prove prediction parity.