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capture

Save decisions, learnings, and task outcomes to persistent memory for later recall. Preserve conversational context and share it with your team to prevent information loss.

Instructions

Save a decision, a learning, or a task outcome to memory. Call this tool after you complete a non-trivial task, make a decision, or fix a bug with a known root cause. You can capture a single text string, or a list of role-based conversation messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags.
typeNoThe type of the memory. Defaults to 'conversation' if omitted.conversation
formatNoThe response format. Use 'json' for structured data (e.g. benchmarks). Defaults to 'text'.text
contentNoThe text to remember. The tool redacts secrets before it stores the text. Use this for a single message. Use 'messages' instead for a multi-turn conversation.
task_idNoThe task ID. Use this to isolate memory by a specific task. Link captures to a task for finer isolation.
team_idNoThe team ID. Use this to isolate memory by team. When set, all queries filter by this value.
user_idNoThe user ID. Use this to isolate memory by user within a team. When set with team_id, queries filter by both.
agent_idNoThe agent ID. Use this to isolate memory by agent role within a team. Defaults to the detected agent.
messagesNoA list of role-based conversation messages to capture. When set, 'content' is ignored. The tool flattens the messages into a single text for search, and stores the original messages for retrieval.
metadataNoOptional metadata.
verifiedNoSet this to true to mark the capture as verified. Verified captures rank higher in recall.
supersedesNoThe ID of a capture that this one replaces. The old capture is marked as stale and ranks lower.
session_keyNoThe session key. The default is hash(cwd).
override_rejectionNoSet this to true to force capture even if the content was previously rejected. Use this only when the rejection reason no longer applies.
Behavior2/5

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

No annotations are provided, so the description carries the full burden. The main description only says 'save ... to memory' and does not disclose important behaviors like secret redaction, the flattening of multi-message captures, or ranking/stale effects. These details are only in the parameter schema descriptions, not the main description.

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?

The description is concise and front-loaded: the first sentence states the purpose, the second gives usage guidance, and the third clarifies input formats. Every sentence earns its place with no redundant filler.

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

Completeness3/5

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

Given the tool's complexity (14 parameters, no annotations, no output schema), the description is adequate for the core use case but does not provide a high-level overview of isolation options (team_id, user_id, agent_id, task_id) or special features like supersedes and override_rejection. The schema descriptions compensate substantially, but the main description could more proactively guide the agent.

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 detailed parameter descriptions. The main description adds marginal value by summarizing the two capture modes ('single text string, or a list of role-based conversation messages'), but this is redundant with the schema's content and messages descriptions. It does not offer new meaning beyond structured fields.

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 states 'Save a decision, a learning, or a task outcome to memory' with a specific verb and resource. It distinguishes from siblings like recall (retrieval) and forget (deletion) by clearly framing this as a write-to-memory operation.

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

Usage Guidelines4/5

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

The description gives explicit usage triggers: 'Call this tool after you complete a non-trivial task, make a decision, or fix a bug with a known root cause.' This provides clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions.

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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