documentation-search

documentation-search is a skill for Claude Code, Codex from caipe-io/ai-platform-engineering. It costs 46 tokens per session (964 once invoked), scanned A, original, Apache-2.0.

A search tool for an internal knowledge base. It finds runbooks, architecture documents, architecture decision records, best practices, and troubleshooting guides using meaning-based search.

In plain words
What is it for?
Use it to answer questions about deployments, rollbacks, architecture decisions, operations, and other documented engineering practices.
Why use it?
It helps locate relevant internal guidance when the exact document name or wording is unknown.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to answer questions about deployments, rollbacks, architecture decisions, operations, and other documented engineering practices.

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Install with agentmods
npx agentmods add skills/caipe-io/ai-platform-engineering/documentation-search
Install

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.

Any agent
npx skills add caipe-io/ai-platform-engineering --skill documentation-search
Clone the repo
git clone --depth 1 https://github.com/caipe-io/ai-platform-engineering

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for documentation-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/caipe-io/ai-platform-engineering/documentation-search.svg)](https://agentmods.dev/skills/caipe-io/ai-platform-engineering/documentation-search)
Your own site
<a href="https://agentmods.dev/skills/caipe-io/ai-platform-engineering/documentation-search"><img src="https://agentmods.dev/badge/skills/caipe-io/ai-platform-engineering/documentation-search.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 964 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.00964
Opus 5 $0.00023 $0.00482
Sonnet 5 $0.00009 $0.00193
Haiku 4.5 $0.00005 $0.00096

Measured 8d ago against content hash fcfbcc542ad9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

documentation-search 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 8d 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.

ui/src/skills/documentation-search/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Search the internal knowledge base using RAG (Retrieval-Augmented Generation) to find relevant runbooks, architecture docs, ADRs, and best practices.

Instructions

Phase 1: Query Understanding

  1. Parse the user's intent:
    • Are they looking for a specific document (e.g., "deployment runbook")?
    • Are they asking a question the docs can answer (e.g., "how do we handle rollbacks?")?
    • Are they exploring a topic (e.g., "what do we know about A2A protocol?")?
  2. Formulate search queries:
    • Extract key terms from the user's question
    • Generate 2-3 variant queries to improve recall
    • Include relevant synonyms (e.g., "deploy" = "release" = "ship")

Phase 2: Knowledge Base Search (RAG Agent)

  1. Search across document sources:
    • Architecture Decision Records (ADRs) in docs/docs/changes/
    • Spec Kit documents in .specify/specs/
    • Runbooks and operational guides
    • README files and inline documentation
    • Confluence pages (if Confluence agent available)
    • Backstage TechDocs (if Backstage agent available)
  2. Rank results by relevance:
    • Exact keyword matches ranked highest
    • Semantic similarity for conceptual matches
    • Recency as a tiebreaker (newer docs preferred)

Phase 3: Answer Synthesis

  1. Direct answer: If the docs contain a clear answer, provide it directly
  2. Compiled answer: If information is spread across multiple docs, synthesize
  3. Source attribution: Always cite which document(s) the answer came from
  4. Gaps identified: Note if the question is only partially answered

Output Format

## Documentation Search Results

**Query**: "How do we handle database migrations?"

### Answer
Based on the internal documentation, database migrations follow this process:

1. Create a migration script using Alembic (see Runbook RB-023)
2. Test in staging environment first (required per ADR-008)
3. Run during the maintenance window defined in the on-call calendar
4. Verify with rollback script before marking complete

### Sources
| Document | Type | Relevance | Last Updated |
|----------|------|-----------|--------------|
| RB-023: Database Migration Runbook | Runbook | High | 2026-01-15 |
| ADR-008: Database Schema Changes | ADR | Medium | 2025-11-20 |
| .specify/specs/db-migration-v2.md | Spec | Medium | 2026-02-01 |

### Key Excerpts
> From **RB-023**: "Always run `alembic upgrade head --sql` first to preview
> the migration SQL before applying. Never run migrations during peak hours."

> From **ADR-008**: "We chose Alembic over Django migrations because our
> services are not Django-based and Alembic provides better raw SQL support."

### Related Topics
- Rollback procedures (see RB-024)
- Schema versioning strategy (see ADR-008)
- Testing database changes (see .specify/specs/db-testing.md)

Read the full file on GitHub · 98 lines

Changes

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.

  1. 8d ago First seen · 98 lines · 46 tokens per session scan A fcfbcc542ad9

Subscribe to this mod's changes

documentation-search is a skill published in the GitHub repository caipe-io/ai-platform-engineering (407 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 964 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.