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mcp_engram_update

Update a stored memory by encoding new text into its provenance log. Avoids history loss from destructive forget+remember operations.

Instructions

CRITICAL: Use whenever you change an existing memory. NEVER forget+remember — destroys history. Superposes q + p-momentum + ProvLog splice. Prefer mcp_engram_update_with_tensor_bond for agent edits (recall-first + lineage bond). FEW-SHOT EXAMPLES: (1) Post-edit arc delta: {"concept":"store__fn__update__arc","new_text":"delta: added verify_edit_lineage helper"} (2) Design evolution: {"concept":"design:agent_tool_fidelity_v1","new_text":"Shipped composite safe_edit_and_verify","provlog_mode":"append"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptYesThe concept name to update
new_textYesDelta or full source text to encode + splice into provlog
provlog_modeNoOptional — default inferred from concept (append for __arc/trace:*; replace for AST __fn__/* with source-shaped text)
Behavior3/5

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

No annotations provided, so description carries burden. It mentions destructive nature of alternative approach and superpositions, but lacks detail on side effects, permissions, or response behavior.

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?

Packed with essential info (warning, usage, examples) in compact form. Some redundancy (e.g., 'NEVER forget+remember' could be integrated), but overall 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 complexity and many siblings, description covers purpose, alternatives, parameter semantics, and provides few-shot examples. Adequately compensates for lack of annotations and output schema.

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%, but description adds meaning: explains new_text as delta or full source, provlog_mode enum, and concept as name to update. Adds value 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?

Clearly states it updates existing memory, warns against forget+remember, and provides specific operations (q+momentum, ProvLog splice). Few-shot examples reinforce 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?

Explicitly mentions when to use this tool vs sibling mcp_engram_update_with_tensor_bond, and advises against forget+remember for history preservation.

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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