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/xobotyi/cc-foundry/skill-engineeringnpx skills add xobotyi/cc-foundry --skill skill-engineeringgit clone --depth 1 https://github.com/xobotyi/cc-foundryWrote 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/xobotyi/cc-foundry/skill-engineering)<a href="https://agentmods.dev/skills/xobotyi/cc-foundry/skill-engineering"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/skill-engineering.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 | $0.00026 | $0.02094 |
| Opus 5 | $0.00013 | $0.01047 |
| Sonnet 5 | $0.00005 | $0.00419 |
| Haiku 4.5 | $0.00003 | $0.00209 |
Grade A, and why
skill-engineering 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 3d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A skill stabilizes a procedure the agent performs unreliably. It is not a place for knowledge the model already has, and it is not documentation. Value concentrates in procedural anchoring — setup order, tool sequence, the check that catches a specific failure — not in explanation.
Decide whether the behavior belongs in a skill
- Write a skill only where the model fails the procedure without it. Skills pay off where the model is weak and cost where it is already competent: a skill on a task the model already handles adds tokens, adds an applicability judgment it can get wrong, and narrows the recovery path it would otherwise have found.
- One skill per procedure a user would name in a single request. If one request needs two of these skills, they are one skill; if one skill answers two unrelated requests, it is two.
- Put a prohibition that must hold every time in a hook. Prose steers; the host's lifecycle mechanism enforces.
- Put work that needs a clean context and returns a summary in a subagent, and connection to an external system in a tool or server. Skills carry procedure; tools carry capability.
Archetype and scoping — the workflow, knowledge, and coding-discipline shapes with their structural templates, the
scope-sizing tests, negative triggers, and skill composition: [${CLAUDE_SKILL_DIR}/references/archetypes.md]. Read it
before writing the body, because the archetype decides the structure.
Write the description as routing code
The description is the only part of a skill that is always in context, and it is where most skills fail: over half of public skills carry routing metadata that cannot route.
- Use the form
[Verb] [what]. Use when [trigger].A description that says only what the skill does gives the model nothing to fire on. - Discriminate against the neighbors. Name the boundary that separates this skill from the sibling that matches the same words. Selection precision collapses as the candidate pool grows — from roughly 30% at five candidates to a few percent at a hundred — so a description competes, it does not merely describe.
- Front-load the use case and keep it under 250 characters. Listings are budgeted and truncate.
- Write the triggers in the words a user would type, including the case where the user never names the domain.
- Keep routing information out of the body and write it in third person. The body is read after the routing decision is made, and a mixed point of view degrades discovery.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 138 lines · 26 tokens per session scan A 5d4e2a110a04
skill-engineering is a skill published in the GitHub repository xobotyi/cc-foundry (20 stars, last pushed 3d ago), licensed MIT. It adds 26 tokens to every session and 2,094 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.
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