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alopez3006

snipara-mcp

by alopez3006

rlm_context_query

Query project documents, parsed business files, and shared context to retrieve ranked sections as source truth and narrative documentation.

Instructions

Query project documents, parsed business files, and shared context. Use this first for source truth and narrative documentation. Returns ranked sections within token budget. If a broad query times out, retry once with a narrow 3-8 term query, max_tokens 800-1500, search_mode='keyword', return_references=true, auto_decompose=false, and include_all_tiers=false. For exact text use rlm_search; for structural code context use rlm_code_neighbors, rlm_code_callers, or rlm_code_imports.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesDocumentation, business-context, or current-truth question. For timeout recovery, narrow this to the key file, feature, symbol, or 3-8 terms.
max_tokensNoToken budget. Use 800-1500 for fast recovery retries after a timeout.
search_modeNoSearch strategy. Use keyword for fast retry/recovery paths; use hybrid for normal documentation discovery.hybrid
include_metadataNo
prefer_summariesNo
return_referencesNoReturn chunk references (IDs + previews) instead of full content. Use rlm_get_chunk to retrieve full content by ID. Reduces hallucination by maintaining clear source attribution and is the preferred fast retry path after a timeout.
auto_decomposeNoAuto-decompose complex queries into sub-queries (Pro+ only). Complex queries (50+ words, multiple questions, comparisons) are automatically broken down and results merged. Set to False for fast timeout recovery retries.
include_all_tiersNoInclude all context tiers including COLD and ARCHIVE. By default, searches only HOT and WARM tiers for faster, more relevant results.
Behavior5/5

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

Describes that it returns ranked sections within a token budget, mentions timeout behavior and retry strategy, and gives specific parameter adjustments for recovery. No annotations to contradict.

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?

Concise five-sentence description that front-loads the purpose, then gives usage guidance and sibling differentiation. No redundant information.

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

Completeness5/5

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

Complete for a query tool with 8 parameters and no output schema. Covers purpose, usage, retry behavior, and alternatives, providing sufficient context for correct selection and invocation.

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 descriptions are already detailed (75% coverage). The description adds value by consolidating a retry strategy with specific parameter values (e.g., max_tokens 800-1500, search_mode='keyword'), going beyond default recommendations.

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?

Clearly states verb 'Query' and specific resources: project documents, parsed business files, shared context. Distinguishes from siblings by mentioning exact text and code structural tools.

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 says 'Use this first for source truth and narrative documentation' and provides a detailed retry strategy for timeouts. Also indicates when to use alternatives (rlm_search, rlm_code_*).

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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