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 jmagly/aiwg --skill validate-componentgit clone --depth 1 https://github.com/jmagly/aiwgWrote 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/jmagly/aiwg/validate-component)<a href="https://agentmods.dev/skills/jmagly/aiwg/validate-component"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/validate-component/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/jmagly/aiwg/validate-component"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/validate-component.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 75 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Rogue Agent · line 192 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- medium Agent Snooping · line 127 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 132 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 154 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 168 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00021 | $0.02108 |
| Opus 5.5 | $0.00008 | $0.00843 |
| Sonnet 5.5 | $0.00004 | $0.00422 |
| Haiku 4.5 | $0.00002 | $0.00211 |
Grade A, and why
validate-component 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 1mo 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validate Component
You check a single AIWG component — a skill, agent, or CLI command — for completeness and correctness, then produce a structured pass/fail report with specific gaps listed.
Triggers
- "validate this skill" → check the skill in the current directory or named path
- "is this component complete" → run completeness check
- "check this agent" → validate agent frontmatter and manifest registration
- "validate component at " → validate the named path
- "is this command wired up correctly" → check CLI command completeness
- "pre-PR check on this skill" → run validate-component
Trigger Patterns Reference
| Pattern | Example | Action |
|---|---|---|
| Validate skill | "validate this skill" | Run skill completeness checks |
| Validate agent | "check this agent definition" | Run agent completeness checks |
| Validate command | "is this command wired up" | Run command completeness checks |
| Path-specific | "validate component at agentic/code/addons/my-addon/skills/my-skill" | Validate at given path |
| Pre-PR | "pre-PR check on this component" | Run all applicable checks |
Process
-
Identify component type and path:
- If no path is given, check the current working directory or the most recently edited file
- Detect type from directory structure:
- Path contains
skills/<name>/SKILL.md→ skill - Path contains
agents/<name>.mdoragents/<name>/→ agent - Component name appears in
src/extensions/commands/definitions.ts→ command
- Path contains
-
Run type-appropriate checks:
For a Skill:
- Read the
SKILL.mdfile - Check:
description:field present in YAML frontmatter - Check:
# Titlesection present - Check:
## Behavioror## Processsection present - Check: At least one
## Examplesentry - Find the parent addon's
manifest.json(walk up directory tree) - Check: Skill name listed in
manifest.jsonskillsarray - Check: File lives in
agentic/code/(not in a provider deployment directory) - If SKILL.md contains
executedViaSkillRunner: truereference: check for circular CLI call pattern - Full link classification check (see Link Classification below)
- Read the
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.
- 1mo ago First seen · 204 lines · 21 tokens per session scan A 47b6a3b823e4
validate-component is a skill published in the GitHub repository jmagly/aiwg (224 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 2,108 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 skills, from other repositories
builder
Implementing robust business logic, API integrations, data models, and reproducible AI image-generation code with type safety. Use for production implementation, Gemini image API pipelines, or interactive pair programming.
matrix
Controlling combinatorial explosion across multi-dimensional axes: minimum coverage sets, execution plans, test/deploy/UX/risk prioritization. Use when scoping multi-axis combinations.
nexus
Orchestrating multi-specialist task chains and scope-adaptive product delivery: classifies intent, selects and executes the minimum viable chain, aggregates results, and verifies acceptance criteria. For multi-domain tasks, build-first delivery, and product lifecycle execution.
oracle
Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.
scribe
Authoring standalone and cross-team specifications: PRD/SRS/HLD/LLD, staged L0-L4 unified packages, BDD acceptance criteria, and traceability. Use for technical or multi-audience documentation; not implementation or architecture decisions.
tome
Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.