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Stale decisions due for revisit

stale_decisions
Read-onlyIdempotent

Identify decisions with past revisit dates that remain actively used. Returns overdue items with reasons and active-use signals to prioritize review.

Instructions

Decisions whose revisit_after has passed AND that are still in active use.

The date-based half of active memory (v0.3.8). Returns events with a revisit_after now in the past — but ONLY when the entity is still live, so an old-but-correct decision nobody touches never nags. The required active-use signal is one of: the entity was queried (blame / diff / prior_attempts) at or after the decision, or its changeset_id saw later activity. Pure age alone does NOT surface.

Each result is the change event plus four fields: revisit_due (UTC ISO), days_overdue (int, 0 on the due day), active_use_signals (list), and stale_reason (a one-line summary). Most-overdue first; filter by entity_path, project, or agent. Date-based only — expires_when evaluation lands in v0.3.11. Templated and deterministic; no LLM call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_pathNoOptional filter to a single entity or path prefix — 'users' also covers 'users.email'. Empty = every entity.
projectNoOptional filter to a specific project/repository.
agentNoOptional filter to the agent that logged the decision.
limitNoMaximum number of results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive. Description adds valuable context on active-use signals, ordering, and output fields. No contradictions.

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?

Clear and well-structured with front-loaded purpose and bullet-style details. Slightly verbose but efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete coverage of filtering logic, active-use signals, output structure, and limitations. Output schema exists, so return values need no extra explanation.

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%. Description restates parameter defaults and filters but adds no new semantics 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 returns decisions with passed revisit_after that are still active, distinguishing it from date-only or age-based alternatives.

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 explains when to use (date-based stale decisions), what it does not do (pure age alone), and notes future features (expires_when in v0.3.11).

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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