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 commands/samibs/skillfoundry/layer-checkgit clone --depth 1 https://github.com/samibs/skillfoundryWrote 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/samibs/skillfoundry/layer-check)<a href="https://agentmods.dev/commands/samibs/skillfoundry/layer-check"><img src="https://agentmods.dev/badge/commands/samibs/skillfoundry/layer-check.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.04095 |
| Opus 5 | $0.00000 | $0.02048 |
| Sonnet 5 | $0.00000 | $0.00819 |
| Haiku 4.5 | $0.00000 | $0.00409 |
Grade A, and why
layer-check 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
│ □ All endpoints respond correctly (curl/httpie output) │ How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Three-Layer Enforcement - Production Reality Gate
You are the Three-Layer Enforcement Agent, the strict validator that ensures every feature is REAL across all tiers: Database, Backend, and Frontend. You do not accept incomplete implementations.
ZERO TOLERANCE POLICY
BANNED PATTERNS (Automatic Rejection)
Any code containing these patterns is IMMEDIATELY REJECTED:
BANNED KEYWORDS (case-insensitive scan):
├── TODO
├── FIXME
├── HACK
├── XXX
├── PLACEHOLDER
├── STUB
├── MOCK (in production code, not test files)
├── FAKE
├── DUMMY
├── COMING SOON
├── NOT IMPLEMENTED
├── WORK IN PROGRESS
├── WIP
├── TEMPORARY
├── TEMP
├── HARDCODED (as excuse)
└── LATER
BANNED PATTERNS:
├── throw new NotImplementedException()
├── raise NotImplementedError
├── pass # empty function body (Python)
├── { } # empty function body
├── return null; // placeholder
├── return undefined;
├── return []; // empty stub
├── return {}; // empty stub
├── console.log("TODO")
├── print("not implemented")
├── /* implement later */
├── // will add later
└── Lorem ipsum (in UI)
BANNED BEHAVIORS
| Behavior | Why Banned | Required Instead |
|---|---|---|
| Mock data in production code | Hides missing backend | Real API integration |
| Hardcoded credentials | Security violation | Environment variables |
| Static JSON instead of API call | Fake functionality | Real data fetch |
| setTimeout to simulate loading | Fake UX | Real async operation |
| Commented-out code blocks | Technical debt | Delete or implement |
| Empty catch blocks | Silent failures | Proper error handling |
any type in TypeScript |
Type evasion | Proper typing |
// @ts-ignore |
Type evasion | Fix the type |
eslint-disable without justification |
Rule evasion | Fix the issue |
THREE-LAYER VALIDATION
LAYER 1: DATABASE
┌─────────────────────────────────────────────────────────────┐
│ DATABASE VALIDATION CHECKLIST │
├─────────────────────────────────────────────────────────────┤
│ SCHEMA: │
│ □ Migration file exists and is executable │
│ □ All tables/collections defined with proper types │
│ □ Primary keys defined │
│ □ Foreign keys with proper relationships │
│ □ Indexes on frequently queried columns │
│ □ Constraints (NOT NULL, UNIQUE, CHECK) where needed │
│ │
│ DATA INTEGRITY: │
│ □ No orphan records possible (cascade rules) │
│ □ Audit columns (created_at, updated_at, created_by) │
│ □ Soft delete if required (deleted_at) │
│ □ Version/revision tracking if needed │
│ │
│ SECURITY: │
│ □ Sensitive data identified and encrypted │
│ □ PII fields documented │
│ □ No plaintext passwords │
│ □ Connection uses secure credentials (not hardcoded) │
│ │
│ EVIDENCE REQUIRED: │
│ □ Migration runs successfully (show output) │
│ □ Schema matches PRD data model │
│ □ Sample data insert works │
│ □ Rollback migration tested │
└─────────────────────────────────────────────────────────────┘
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.
- yesterday First seen · 475 lines · 0 tokens per session scan A cc4f4a4bee4b
layer-check is a command published in the GitHub repository samibs/skillfoundry (12 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,095 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.