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knowledge-base-search

Search and locate relevant content within a local knowledge base (files, indices, or PageIndex)

Install / Use

npx skills add aipoch/medical-research-skills --skill knowledge-base-search

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Supported Platforms

Universal

Our assessment of knowledge-base-search

knowledge-base-search scores 86/100 on our quality scale, 167th of 274 Customer Support skills we index.

Its SKILL.md is 6.2 KB long, well organised into 11 sections with 1 code example: a thorough specification that gives an agent plenty to work with.

With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
17/20
Description
12/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 13 days ago, so knowledge-base-search is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

knowledge-base-search compared with similar skills

All 4 of these similar skills score higher than knowledge-base-search; compare them before choosing.

SkillScoreStarsUpdatedFormat
knowledge-base-search (this skill)by aipoch861.9k13d agoSKILL.md
Agent-Reachby Panniantong10086.4k15d agoCLAUDE.md
algorithmic-artby anthropics100177.9k8d agoSKILL.md
pptxby anthropics100177.9k8d agoSKILL.md
designby nextlevelbuilder100130.2k9d agoSKILL.md

Frequently asked questions

How do I install knowledge-base-search?
Run npx skills add aipoch/medical-research-skills --skill knowledge-base-search. The install tabs above show the steps for each supported agent.
Which AI agents does knowledge-base-search work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is knowledge-base-search safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is knowledge-base-search still maintained?
The repository was last updated 13 days ago, so knowledge-base-search is actively maintained.

name: knowledge-base-search description: Search and locate relevant content within a local knowledge base (files, indices, or PageIndex). Use when you need verifiable citations (file + page/paragraph) to support answers from local sources. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Knowledge Base Search

When to Use

  • You need to find specific facts, definitions, or procedures from a local knowledge base and return the exact source location.
  • You must provide traceable citations (file path + page/paragraph/section) for audit, compliance, or review.
  • You need to verify the original wording of a claim in the source document (quote-level validation).
  • You want to compare how multiple local documents discuss the same topic and identify differences.
  • You need to assemble supporting snippets for a report, FAQ, or internal knowledge response using only local materials.

Key Features

  • Supports multiple retrieval approaches: direct file search, index-based search, and PageIndex-style location mapping.
  • Query strategy guidance: keyword splitting, synonym expansion, and optional filters (time range, file type, tags).
  • Relevance-oriented result ranking and filtering to keep the most supportive evidence first.
  • Outputs verifiable hit snippets with precise citation locations (file + page/paragraph/section when available).
  • Enforces local-only boundaries: searches only within authorized directories and does not modify source content.

Dependencies

  • glob (>= 10.0.0): file path pattern matching
  • grep (>= 3.11): in-file text searching
  • Local knowledge base index files (one or more of: filename index, content index, vector index, PageIndex mapping)
  • assets/hit_list_template.csv: standardized hit list output template
  • Optional reference: references/guide.md (output formats, checklists, inspection points)

Example Usage

The following example demonstrates an end-to-end local search workflow and produces a CSV hit list compatible with assets/hit_list_template.csv.

Inputs

  • Knowledge base root: ./kb/
  • Query: How do we rotate API keys?
  • Filters: file types md,pdf, time range 2024-01-01..2026-12-31

Steps

  1. Confirm index and scope

    • Ensure the search scope is limited to authorized paths (e.g., ./kb/).
    • Identify available indices:
      • filename/content index (fast keyword search)
      • vector index (semantic retrieval)
      • PageIndex mapping (page/paragraph location resolution)
  2. Build the query

    • Keywords: rotate, API key, key rotation
    • Synonyms/variants: credential rotation, token rotation, regenerate key
    • Filters:
      • file type: *.md, *.pdf
      • time range: 2024-01-01..2026-12-31 (if metadata exists)
  3. Execute search (local-only)

    • Path discovery (example):
      • glob("./kb/**/*.md")
      • glob("./kb/**/*.pdf")
    • Content search (example):
      • grep -RIn "API key\|key rotation\|rotate" ./kb/
  4. Filter and rank results

    • Keep hits that directly answer the question (procedure, policy, steps, constraints).
    • Rank by:
      • term proximity (e.g., “rotate” near “API key”)
      • section relevance (e.g., “Security”, “Credentials”, “Operations”)
      • coverage (hits that include prerequisites + steps + verification)
  5. Output citations and hit list

    • For each hit, output:
      • file_path
      • location (page number for PDFs; heading/paragraph index for Markdown; PageIndex if available)
      • snippet (verbatim excerpt supporting the conclusion)
      • notes (why it is relevant; any assumptions)
    • Save as hit_list.csv using assets/hit_list_template.csv columns.

Example Output (CSV rows)

file_path,location,snippet,relevance_score,notes
kb/security/credential_policy.pdf,page 12,"API keys must be rotated every 90 days... Rotation requires...",0.92,"Direct policy + rotation interval + procedure reference."
kb/runbooks/api_key_rotation.md,section 'Procedure' ¶3,"To rotate an API key: (1) create a new key... (2) update services... (3) revoke old key...",0.89,"Step-by-step operational runbook."
kb/audit/controls.md,heading 'Key Management' ¶2,"Evidence of rotation includes change tickets and key revocation logs...",0.81,"Provides verification/evidence requirements."

Implementation Details

Retrieval Workflow

  1. Index confirmation

    • Determine knowledge base root paths and last update time (if available).
    • Detect which indices exist:
      • filename index: quick narrowing by file names
      • content index: inverted index / grep-like scanning
      • vector index: semantic similarity retrieval
      • PageIndex: mapping from document offsets to page/paragraph identifiers
  2. Query strategy

    • Tokenize the question into:
      • core entities (e.g., “API key”)
      • actions (e.g., “rotate”, “revoke”, “regenerate”)
      • constraints (e.g., “every 90 days”, “approval required”)
    • Expand with synonyms and variants.
    • Apply filters when metadata exists:
      • time range
      • file type
      • tags/collections
  3. Result filtering and ranking

    • Remove low-signal hits (navigation, boilerplate, unrelated mentions).
    • Rank by a weighted score (example):
      • Keyword match (exact phrase > partial): 0.45
      • Proximity (terms close together): 0.20
      • Section importance (titles like “Procedure/Policy”): 0.20
      • Coverage (answers include steps + constraints + verification): 0.15
    • Keep the original text snippet verbatim for verification.
  4. Citation and location resolution

    • Markdown/text:
      • use heading + paragraph index (or line range) as the primary locator
    • PDF:
      • use page number; optionally include bounding text around the hit
    • PageIndex (if present):
      • map internal offsets to stable page/paragraph identifiers

Constraints and Limitations

  • Search only within user-authorized local directories.
  • Do not modify source documents.
  • Do not execute scripts or arbitrary code.
  • Do not access network resources or external APIs.
  • If indices are missing/corrupted, fall back to direct file scanning; if scanning is not possible, report the limitation and required remediation (re-indexing).

Related Skills

View on GitHub
GitHub Stars1.9k
CategoryCustomer
Updated13d ago
Forks175

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions