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mcp_engram_remember_solution

Store a verified error pattern and its solution as a crystallized pair for future recall. Use after confirming a fix to build durable memory of resolved issues.

Instructions

Crystallized error→solution pair (ZEDOS_PRAXIS, CRS=1.0). Use after verified fixes, not for routine deltas (use update). FEW-SHOT EXAMPLES: (1) Build fix: {"error_pattern":"cargo test mcp mutex poison","solution":"Use mcp_test_guard() serializing MCP tests"} (2) Ritual fix: {"error_pattern":"repeated context_for_edit blocked","solution":"mcp_engram_update on __arc or mcp_engram_ack_edit_arc before re-read","process_context":"process:engram.ritual.working-memory"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
solutionYesThe solution or approach that resolved it
error_patternYesThe error or problem pattern (error message, concept, or description)
process_contextNoOptional process:engram.* key — emits realized_by edge (WS-3)
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions 'crystallized' and 'CRS=1.0' without explanation, and does not describe side effects, whether it overwrites, or any error handling. The examples are domain-specific jargon. The agent is left without understanding key behaviors like idempotency or success/failure outcomes.

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 relatively concise with a clear structure: purpose, usage guidelines, then examples. It is front-loaded. However, the examples are lengthy and embedded, slightly reducing conciseness. Overall well-organized.

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?

With no output schema and 3 parameters (100% schema coverage), the description covers when to use the tool and provides examples, but it lacks details about the tool's return value, idempotency, or behavior on duplicate entries. The jargon (ZEDOS_PRAXIS, CRS) is unexplained. It is adequate but leaves gaps for an agent to fully understand the tool's contract.

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%, so baseline is 3. The description adds value by providing few-shot examples that demonstrate realistic parameter values, and it explains that the optional 'process_context' parameter emits a 'realized_by' edge (WS-3), which goes beyond the schema description. This clarifies the meaning and usage of parameters beyond mere field definitions.

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 tool is for storing 'crystallized error→solution pair' with a defined framework (ZEDOS_PRAXIS, CRS=1.0). It distinguishes itself from sibling tools like mcp_engram_update by specifying it is for verified fixes, not routine deltas. The few-shot examples further solidify the purpose.

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?

Explicit guidance: 'Use after verified fixes, not for routine deltas (use update).' This tells the agent exactly when to use this tool and provides an alternative (update) for other cases. The examples also illustrate appropriate usage contexts.

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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