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Stateless Agent Memory Engine (SAME)

save_decision

Idempotent

Log project decisions with details, status, and attribution to maintain a searchable record for future reference and continuity.

Instructions

Log a project decision. Appends to the decision log so future sessions can find it.

Args: title: Short decision title (e.g. 'Use JWT for auth') body: Full decision details — what was decided, why, alternatives considered status: Decision status — 'accepted', 'proposed', or 'superseded' (default 'accepted') agent: Optional writer attribution stored in frontmatter (e.g. 'codex')

Returns confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesShort decision title
bodyYesFull decision details
statusYesaccepted, proposed, or superseded (default accepted)
agentNoOptional writer attribution (e.g. codex)
Behavior4/5

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

Annotations provide idempotentHint=true and destructiveHint=false, indicating safe, repeatable operations. The description adds valuable context beyond annotations: it specifies that the action 'Appends to the decision log' (clarifying the append behavior) and mentions storage details ('stored in frontmatter'), which are not covered by annotations. No contradiction with annotations exists.

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 appropriately sized and front-loaded, with the core purpose in the first sentence. The Args and Returns sections are structured but slightly verbose in repeating schema info. Most sentences earn their place by adding context or examples, though some redundancy exists.

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 the tool's moderate complexity, rich annotations (idempotent, non-destructive), and full schema coverage, the description is largely complete. It explains the tool's purpose, behavior, and parameters adequately. The lack of an output schema is mitigated by the 'Returns confirmation' note, though more detail on the confirmation format would enhance completeness.

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 description coverage is 100%, with all parameters well-documented in the schema. The description repeats some parameter details (e.g., 'Short decision title') but adds minimal extra semantics, such as example values for 'title' and clarifying 'agent' usage. This meets the baseline for high schema coverage without significant enhancement.

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 with a specific verb ('Log') and resource ('project decision'), and distinguishes it from siblings by specifying it 'Appends to the decision log' for future sessions. This differentiates it from other save/note tools like save_note or save_kaizen by focusing on decision logging.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context ('so future sessions can find it') but does not explicitly state when to use this tool versus alternatives like save_note or save_kaizen. It provides a general purpose but lacks explicit guidance on exclusions or comparisons with sibling tools.

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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