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mcp_engram_remember

Encode new facts into persistent holographic blocks. Recalls existing memories first; if a similar fact exists (match > 0.85), uses update tool instead to prevent duplicates.

Instructions

Encode NEW facts only — persistent HolographicBlock (.leg3). Recall first; if match>0.85 use mcp_engram_update instead. CRS tiers: 1.0=pinned | >=0.74=grounded | <0.50=verify first. FEW-SHOT EXAMPLES: (1) New harness concept: {"concept":"harness:agent_tool_fidelity_v1","text":"Deterministic suite for edit/update tool fidelity >=95%."} (2) User preference: {"concept":"user__prefers_absolute_paths","text":"Always pass absolute paths to context_for_edit and safe_edit_and_verify."}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text content to encode. Be specific and self-contained — this text must make sense when read in isolation in a future session.
conceptYesUnique snake_case identifier (e.g. 'api_auth_pattern', 'user_prefers_dark_mode'). Use namespacing for related concepts: 'project__component__detail'.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses persistence, file format (.leg3), and CRS tiers. It doesn't mention error conditions or side effects but is sufficiently transparent for a 'remember' operation.

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 front-loaded with purpose, followed by usage guidelines, CRS tiers, and examples. It is slightly long but every sentence adds value, so it remains efficient.

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?

Given no output schema and many sibling tools, the description provides sufficient context with examples, usage rules, and thresholds. It lacks return value details but is complete enough for an agent.

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?

With 100% schema description coverage, baseline is 3. The description adds meaningful guidance: 'Be specific and self-contained' for text and snake_case naming with namespacing for concept, which enhances understanding beyond 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 the tool's purpose: 'Encode NEW facts only' and contrasts it with the sibling tool mcp_engram_update based on recall match threshold. The examples further clarify the intended use.

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 tells when to use this tool: only for new facts, and provides an alternative (mcp_engram_update) when recall match > 0.85. It also includes CRS tier thresholds for guidance.

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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