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/stchiotis/library-first-engineering/lfe-scoutnpx skills add StChiotis/Library-First-Engineering --skill lfe-scoutgit clone --depth 1 https://github.com/StChiotis/Library-First-EngineeringWrote 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/stchiotis/library-first-engineering/lfe-scout)<a href="https://agentmods.dev/skills/stchiotis/library-first-engineering/lfe-scout"><img src="https://agentmods.dev/badge/skills/stchiotis/library-first-engineering/lfe-scout.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 5.1 | $0.00030 | $0.00408 |
| Opus 5 | $0.00015 | $0.00204 |
| Sonnet 5 | $0.00006 | $0.00082 |
| Haiku 4.5 | $0.00003 | $0.00041 |
Grade A, and why
lfe-scout 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 5d 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.
What it actually says
LFE Scout Mode — The Flyweight Path
Position in Pipeline
- Phase: 0.5 (Complexity Gate → Minor Fix path)
- Persona: Scout
- Trigger: Human selects "Minor Fix" at Complexity Gate
- Output: Maintenance Report → Archivist handoff
Mission
Perform rapid, non-architectural maintenance tasks (typos, UI tweaks, simple bug fixes).
🛡️ The Protective Layer
Before taking ANY action, perform a Structural Integrity Check:
- Is this structural? If the task requires adding, deleting, or renaming a file, REJECT and escalate to
/lfe-architect. - Is this root-level? If the task modifies a configuration file at the root (e.g., a root agent-config file,
package.json), REJECT and escalate. - Is this domain-heavy? If the task changes core logic as defined in
CONTEXT.md, REJECT and escalate.
Protocol
- Analyze: Identify the specific lines to change.
- Execute: Implement the fix directly using
replace_file_content. - Report: Output a Maintenance Report including:
- Action: What was changed?
- Rationale: Why was it non-architectural?
- Integrity Check: Confirm no files were added/deleted.
- Log: Update the
CHANGELOG.md. - Update Pipeline: Increment session count in
pipeline_status.md.
Handoff
Signal transition to Archivist for doc sync. Ask the human if they want to run /lfe-hygiene or if the mission is complete.
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.
- 5d ago First seen · 35 lines · 30 tokens per session scan A c1f1ba95c5e4
lfe-scout is a skill published in the GitHub repository StChiotis/Library-First-Engineering (43 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 408 once invoked, about $0.0002 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.
Other skills, from other repositories
playwright
Use when the task requires capturing or automating a real browser from the terminal.
ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
implementation-final-review
Perform the repository's risk-tiered independent final review before implementation completion. Use only when explicitly invoked or when repository instructions require it after behavior-impacting implementation work; audit the complete task diff, supported contracts, lifecycle and security boundaries, complexity, and…
redteam-plugin-development
Standards for creating redteam plugins and graders. Use when creating new plugins, writing graders, or modifying attack templates.
promptfoo-provider-setup
Configure promptfoo providers or redteam targets for hosted models, live HTTP APIs, Python/JavaScript local scripts, agent SDKs, or multi-input systems. Use when connecting promptfoo to the system under test, mapping vars, auth env vars, request bodies, response transforms, or static-code-derived provider wrappers. Do…
search-params
URL search param and hash state management. Use when adding or modifying URL search params, working with useSearchParams, setSearchParams, useSearchParamState, or navigate() with query strings or hash fragments, or fixing browser back/forward button issues.