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A local-first AI agent leveraging MCP servers, running entirely on local hardware with llama.cpp and aggressive quantization for privacy and efficiency
YMCA defines 2 tools with reasonable structure but notable gaps in schema completeness and parameter documentation. retrieve_memory has a well-documented input schema with clear guidance on query quality (e.g., differentiating GOOD vs BAD examples), while store_memory lacks detail on output behavior and error cases. Both tools have solid descriptions (180+ chars each), but neither explicitly documents return types or error classification patterns. The naming convention is verb_noun compliant (retrieve_, store_) and unambiguous. However, parameter descriptions lack specificity about format constraints, valid ranges, or dependency relationships. max_results accepts 1-10 but lacks explicit bounds validation guidance. The 'context' parameter in store_memory is optional but lacks guidance on when it's essential. No parameter validation rules, no recovery guidance for errors, and no indication of idempotency. These gaps align with common community-server issues: descriptions exist but param-level detail and error handling are underspecified.
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Store NEW important information in long-term memory. ONLY use this for information that is NOT already in memory and is worth remembering for future conversations. DO NOT store trivial facts, temporary information, or duplicates of existing memories. Always check memory first with retrieve_memory before storing.
No documented output schema for either tool. LLMs cannot infer what fields retrieve_memory returns (e.g., does it return {results: [{id, text, score}]} or a flat list?) or what store_memory returns on success (confirmation, ID, metadata?). This violates pattern:tool requirement that all tools document output structure.
max_results parameter in retrieve_memory specifies range 1-10 in description but lacks explicit validation constraint in schema or guidance on what happens if an LLM passes an out-of-range value.
store_memory 'context' parameter is optional but lacks guidance on when it is necessary or beneficial. No indication of whether context is only metadata or affects retrieval. Undocumented parameter relationships violate pattern:tool-description requirement that all parameters have actionable descriptions.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 54 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 22 | - | v1 |
No error handling documentation. What happens if retrieve_memory finds no matching documents? Does it return an empty list, a null, or an error? What if store_memory receives duplicate information, is that retried, rejected, or silently ignored? Per pattern:recovery-guide, errors must guide the LLM on what to do next.
No indication of idempotency. Can store_memory be safely retried on failure without creating duplicate entries? Is retrieve_memory read-only (clearly yes from the Risk field, but not stated in description). Agents need explicit idempotency guarantees per pattern:idempotent-operation.