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vectr_fetch

Read-onlyIdempotent

Retrieve a specific code chunk using its chunk id from prior search results to restore it into context without re-running searches or re-reading files.

Instructions

Deterministic re-fetch of a code chunk by its exact id — no embedding, no rerank, just the chunk. Every vectr_search/vectr_locate/vectr_trace result carries its chunk's id (the file:start-end shown in the result header). Use this to restore a chunk that was cleared from your context (by tool-result eviction, context compaction, or a context-editing tombstone) instead of re-running vectr_search or re-reading the whole file. NOT for finding NEW content — use vectr_search for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesChunk ids to restore, exactly as shown in a prior search/locate/trace result (e.g. 'src/auth.py:10-20').
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds that the operation is 'deterministic', 'no embedding, no rerank', and explains the id format 'file:start-end' from prior search results. No contradictions.

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

Conciseness5/5

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

Four tightly-packed sentences with zero waste. The most critical information (purpose and when to use) is front-loaded, followed by the id format reference and a clear exclusion statement.

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

Completeness4/5

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

No output schema, but the tool's behavior is simple. The description covers purpose, usage context, parameter semantics, and safety (via annotations). It could optionally describe the return format, but the current content is sufficient given the low complexity.

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

Parameters4/5

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

Schema coverage is 100% with a description for the 'ids' parameter. The tool description adds valuable context about the id format and provenance ('exactly as shown in a prior search/locate/trace result'), going beyond the schema.

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 'Deterministic re-fetch of a code chunk by its exact id' and distinguishes from siblings by explicitly naming vectr_search, vectr_locate, and vectr_trace for finding new content. The verb 're-fetch' and resource 'code chunk' are specific.

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?

Explicitly states when to use: 'restore a chunk that was cleared from your context' and when not to: 'NOT for finding NEW content — use vectr_search for that'. Provides concrete alternatives, making selection straightforward.

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

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