Skip to main content
Glama

rebuild_vault

Rebuild the vault and search index from an existing explanations file, skipping LLM summaries to re-index after code changes without additional cost.

Instructions

Rebuild the vault and search index from an existing explanations file.

Use this to re-run vault generation WITHOUT making any Claude CLI calls for file summaries. Useful when you want to re-index after code changes but already have summaries, or to iterate on vault structure without LLM cost.

extra_frontmatter_json — optional JSON object of extra fields to add to every vault note's frontmatter, e.g. '{"project": "myapp", "status": "draft", "tags": ["backend", "python"]}'. Strings, numbers, booleans, and flat lists are all supported.

Note: ChromaDB question generation still calls Claude once per chunk — only the file/directory summaries are skipped (they're loaded from JSON).

The explanations.json is saved automatically by ingest_repo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathYes
vault_output_pathNo
explanations_json_pathYes
extra_frontmatter_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, but the description discloses that file/directory summaries are loaded from JSON (skipping Claude calls) while explaining that ChromaDB question generation still requires a Claude call per chunk. This provides valuable behavioral insight beyond the input schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately sized and front-loaded with the main purpose. It is structured into clear paragraphs (purpose, usage, parameter detail, additional note). Every sentence adds value, though some parameter details could be more succinct.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters, no annotations, and an output schema (not shown), the description covers usage context and one parameter well but omits details for other parameters and potential side effects (e.g., overwriting existing vault). It is sufficient but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides detailed semantics only for extra_frontmatter_json (type, example, supported data types) and explains explanations_json_path's origin. However, repo_path and vault_output_path lack any description beyond their names, leaving significant gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (rebuild) and resource (vault and search index) with specific context (from an existing explanations file). It distinguishes from siblings like ingest_repo and sync_vault by highlighting the avoidance of Claude CLI calls for file summaries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: to re-run vault generation without making Claude CLI calls for file summaries, such as after code changes or to iterate on vault structure without LLM cost. It also notes that ChromaDB still calls Claude once per chunk, setting clear expectations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Ayush-Sadekar/codelore-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server