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/haabe/mycelium/delivery-bootstrapnpx skills add haabe/mycelium --skill delivery-bootstrapgit clone --depth 1 https://github.com/haabe/myceliumWrote 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/haabe/mycelium/delivery-bootstrap)<a href="https://agentmods.dev/skills/haabe/mycelium/delivery-bootstrap"><img src="https://agentmods.dev/badge/skills/haabe/mycelium/delivery-bootstrap.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 | $0.00027 | $0.02256 |
| Opus 5 | $0.00014 | $0.01128 |
| Sonnet 5 | $0.00005 | $0.00451 |
| Haiku 4.5 | $0.00003 | $0.00226 |
Grade A, and why
delivery-bootstrap 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 4d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delivery Bootstrap Skill
Just-in-Time tech stack detection and setup.
Workflow
- Check product_type from
.claude/diamonds/active.yml:- If
product_typeis set (from/mycelium:interview), use it to determine the delivery profile. - If not set, scan for indicators per
${CLAUDE_PLUGIN_ROOT}/jit-tooling/detector.mdStep 1b:- Curriculum/lesson plans, LMS config ->
content_course - Manuscript/chapters, editorial calendar ->
content_publication - Video scripts, subtitle files, podcast RSS ->
content_media - Prompt templates, model configs, agent definitions ->
ai_tool - Service blueprints, pricing docs ->
service_offering
- Curriculum/lesson plans, LMS config ->
- If non-software product_type detected: skip software tooling detection (Steps 2-3 below), configure product-type-appropriate validation instead, and proceed to Step 4.
- If
1b. Scan project root for technology indicators (software and ai_tool with code):
- Package files: package.json, Cargo.toml, go.mod, requirements.txt, pyproject.toml, Gemfile, pom.xml, build.gradle
- Config files: tsconfig.json, .eslintrc, .prettierrc, rustfmt.toml, .editorconfig
- CI/CD: .github/workflows, .gitlab-ci.yml, Jenkinsfile, Dockerfile
- Framework indicators: next.config.js, nuxt.config.ts, angular.json, etc.
-
Identify stack components (software/ai_tool with code):
- Language(s) and version(s)
- Framework(s)
- Package manager
- Test runner and framework
- Linter and formatter
- Build tool
- CI/CD platform
- Database (if detectable)
- Deployment target
-
Verify tooling works:
- Run build command
- Run test command
- Run lint command
- Note any failures or warnings
3a. Offer the feedback-loop tooling menu (OFFER-MENU layer):
- For the detected stack, present the best-practice menu from
${CLAUDE_PLUGIN_ROOT}/jit-tooling/security-scanning.md(SAST, dep audit, secrets, test runner, linter), ordered smallest-friction first (typically: secrets scan → linter → SAST → dep audit → container scan). - Frame as: "Best practice is to have tools help you shorten the feedback loop. For your detected stack ({lang}), the menu is: {list}. Want help finding and configuring any of these?"
- Never auto-install. Never pick rulesets on the user's behalf. Adoption is per-tool, per-consent. The user owns the choice. See
feedback-jit-nudge-not-push(founder principle, 2026-05-26). - If user declines or defers, record the offer in
active-stack.ymlundertooling_offers_declinedwith timestamp — later shape-triggers (Step 3b) can re-surface the relevant subset.
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.
- 4d ago First seen · 152 lines · 27 tokens per session scan A f1793cd4b21b
delivery-bootstrap is a skill published in the GitHub repository haabe/mycelium (45 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 2,256 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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