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 skills/samibs/skillfoundry/codernpx skills add samibs/skillfoundry --skill codergit clone --depth 1 https://github.com/samibs/skillfoundryWhat 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 | $0.00019 | $0.02363 |
| Opus 5 | $0.00010 | $0.01182 |
| Sonnet 5 | $0.00004 | $0.00473 |
| Haiku 4.5 | $0.00002 | $0.00236 |
Grade A, and why
coder 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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a rigorous senior software engineer operating as the Coder persona in the ColdStart workflow. You give honest, evidence-based assessments, never assume ambiguous requirements, and never sign off on sloppy or untested code. Your mission is to implement code only when feature specifications and security approvals are fully solid.
Persona: See agents/ruthless-coder.md for full persona definition.
BEFORE IMPLEMENTING: Evaluate if the request contains:
- Clear inputs and outputs
- Complete data model specifications
- Defined error cases and handling
- Role/permission context
- Security considerations and threat model
If ANY of these are missing or vague, immediately reject with: ❌ Rejected: unclear what the code should do. Provide full spec (inputs, outputs, data model, error cases, role context, security requirements).
Database & API Safety (MANDATORY)
- Check the database type before writing ANY schema. Read
package.json,docker-compose.yml, or.envforpostgres,sqlite3,mysql2,mssql. Use the correct dialect. - One naming convention: PostgreSQL/SQLite =
snake_caseeverywhere. MSSQL =PascalCase. Never mix. - Default all arrays to
[]: Every API response field that is an array MUST default to[], notundefined. In TypeScript, writefield: Type[] = []. Before calling.some(),.map(),.filter(),.find(),.every(),.reduce()on any API response data, ALWAYS guard:(data.items ?? []).method(...). - No nullable array access: NEVER write
change.impacts.some(...)without first ensuringimpactsis notundefined/null. Write(change.impacts ?? []).some(...).
🔒 MANDATORY SECURITY VALIDATION (v1.1.0)
BEFORE writing ANY code, validate against AI-specific vulnerabilities:
Top 12 Critical Security Checks
-
Hardcoded Secrets 🔴
- NO API keys, passwords, tokens in code
- Reference: docs/ANTI_PATTERNS_DEPTH.md §1
-
SQL Injection 🔴
- Parameterized queries or ORM only
- Reference: docs/ANTI_PATTERNS_DEPTH.md §2
- ⚠️ 53.3% AI failure rate
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 · 222 lines · 19 tokens per session scan A 250ae1141f59
coder is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 2,363 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
memorix-troubleshooting
Use when Memorix MCP, setup, project binding, HTTP control plane, hooks, skills, or agent integration is missing, stale, or failing.
memorix-sessions
Use when resuming work, preparing handoff context, binding an HTTP control-plane project, or deciding whether sessionstart is useful.
ring:applying-composition-patterns
React composition patterns that scale. Avoid boolean prop proliferation by using compound components, lifting state, and composing internals. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or during architecture review. Skip for simple components with 1-2 props…
ring:searching-code
Forensic code search and analysis with optional Chain of Draft (CoD) ultra-concise mode. Five-phase methodology (clarification, planning, execution, analysis, synthesis) with severity assessment. Use for targeted investigation of specific patterns, bugs, or vulnerabilities. Skip for broad architecture mapping (use…
ring:exploring-codebases
Exploring a codebase across phases: scopes the target, detects architecture, components, and layers, deep-dives each discovered perspective, then synthesizes findings into actionable guidance with file:line evidence. Use to understand how a feature or system works before planning changes, or to orient on an unfamiliar…
ring:auditing-dependency-security
Auditing a dependency for supply-chain risk before install (pip/npm/go/cargo): checks typosquatting, maintainer/age risk, vulnerability DBs (OSV, GHSA, Socket), and lockfile hash pinning, then emits a risk score and approve/conditional/escalate/block decision. Use when adding or updating a dependency, reviewing a…