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remember_decision

Read-onlyIdempotent

Capture decisions in real time during a session. Writes to a knowledge graph with confidence scoring, routing high-confidence entries directly and queuing mid-confidence ones for review.

Instructions

Live agent write into the decision knowledge graph. Confidence-scores the input and routes it through the memoir review queue: high-confidence rows enter the active graph immediately, mid-confidence rows queue for human approval, low-confidence rows are dropped without persistence. Per-session dedup + rate-limit. Use during a session to capture decisions in real time. For manual high-confidence writes use add_decision; for post-hoc extraction from session logs use mine_sessions. Returns JSON: { id, review_status, confidence, deduplicated? }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesShort summary of the decision
contentYesFull decision text — reasoning, context, tradeoffs
typeYesDecision type
service_nameNoSubproject name this decision is about (e.g., "auth-api", "user-service")
symbol_idNoSymbol FQN this decision is about (e.g., "src/auth/provider.ts::AuthProvider#class")
file_pathYesFile path this decision is about
tagsNoTags for categorization (e.g., ["auth", "security"])
session_idNoSession identifier for dedup/rate-limit (default: "_default")
git_branchNoGit branch this decision belongs to. Omit to auto-detect, or pass null to make it branch-agnostic.
Behavior1/5

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

Contradicts annotations: description says 'Live agent write' but annotations have readOnlyHint=true. Also mentions confidence routing, dedup, and rate-limit, but contradiction overrides.

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, front-loaded with key purpose, then behavioral details and return format. No wasted words.

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?

Covers routing, dedup, rate-limit, and return format. Lacks specifics on rate limit but sufficient for an agent to use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline 3. Description adds minimal parameter-specific value beyond what's in 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 writes decisions into the knowledge graph in real time, and distinguishes from add_decision and mine_sessions with specific use cases.

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 when to use (during session for real-time capture) and provides alternatives for manual high-confidence writes (add_decision) and post-hoc extraction (mine_sessions).

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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