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/d-padmanabhan/agent-engineering-handbook/javascriptgit clone --depth 1 https://github.com/d-padmanabhan/agent-engineering-handbookWhat 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 | $0.00016 | $0.00407 |
| Opus 5 | $0.00008 | $0.00204 |
| Sonnet 5 | $0.00003 | $0.00081 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
javascript 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 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- **Critical**: injection, SSRF, unsafe `child_process` usage, secrets in logs, auth/authz mistakes What it actually says
JAVASCRIPT MODE ACTIVATED
You are now in JAVASCRIPT MODE. Any work on JavaScript MUST follow:
rules/225-javascript-typescript.mdc(shared JavaScript/TypeScript safety and type gates)rules/100-core.mdc(minimal, production-ready changes)rules/310-security.mdc(no secrets, OWASP-minded)
Use this command when the user asks to:
- Create new JS modules/functions
- Modify existing JS code
- Review JS code for correctness/security/performance
Guardrails (mandatory)
- Prefer
async/await; avoid callbacks unless required. - Validate external input; avoid injection in templating/queries/commands.
- Avoid adding dependencies unless necessary.
- Don’t log secrets; redact tokens/headers.
Step 0: Determine intent (create vs modify vs review)
Infer intent from the user’s request. If ambiguous, ask ≤3 clarifying questions (runtime, module system, build tooling, Node/browser target).
Create
Produce complete code with:
- Clear exports
- Error handling
- JSDoc +
@ts-checkfor production JavaScript (per225-javascript-typescript.mdc)
Modify
- Minimal diffs
- Preserve behavior unless requested
- Keep API compatibility unless requested to break it
Review
Prioritize:
- Critical: injection, SSRF, unsafe
child_processusage, secrets in logs, auth/authz mistakes - Recommended: performance hotspots, poor error handling, missing input validation
- Optional: style/readability
Verification (as applicable):
pre-commit run --all-files
Done condition
End with:
- Files changed (or “no changes made”)
- How to validate (lint/tests/build) and expected behavior
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 · 64 lines · 16 tokens per session scan A e4dd1bd06524
javascript is a command published in the GitHub repository d-padmanabhan/agent-engineering-handbook (15 stars, last pushed 2d ago), licensed MIT. It adds 16 tokens to every session and 407 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.