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Remember

chaoscore_remember
Idempotent

Save key-value data to persistent memory for later retrieval, overwriting existing keys and updating timestamps. Optionally add tags or TTL for controlled recall.

Instructions

Persist a key/value record to Semantic Memory (durable, SQLite-backed), so it can be retrieved later with chaoscore_recall — in this session, in a future session, after a server restart, and from either transport. Writing to an existing key overwrites its value and updates its timestamp, making chaoscore_remember idempotent for a given key/value pair.

Memory is a property of the deployment, not of the connection: a record written over stdio is readable over HTTP and vice versa, provided both point at the same database file.

Args:

  • key (string, 1-200 chars): Unique identifier for this memory

  • value (string): The content to remember

  • tags (array of strings): Optional tags for filtering later (default: [])

  • ttl_seconds (number, optional): If set, the record is treated as expired (and excluded from chaoscore_recall) after this many seconds

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: For JSON format: { "key": string, "value": string, "tags": string[], "createdAt": string, "updatedAt": string, "expiresAt": string | null }

Examples:

  • Use when: "Remember that the staging DB uses the Melbourne region" -> key="staging.region", value="Melbourne (australiaeast)"

  • Don't use when: You need to search existing memories -> use chaoscore_recall instead

Error Handling:

  • Returns "Error: ..." with the underlying SQLite error message if the write fails (e.g. disk full, path unwritable)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesUnique key for this memory. Writing an existing key overwrites its value.
tagsNoOptional tags for later filtering with chaoscore_recall
valueYesThe content to remember
ttl_secondsNoOptional time-to-live in seconds. Omit for a record that never expires.
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior5/5

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

Annotations already indicate idempotent, non-read-only, and non-destructive. The description goes further: it explains durable SQLite-backed storage, persistence across sessions/restarts/transports, overwrite semantics with timestamp updates, TTL behavior (exclusion from recall), and error handling. This exceeds annotation coverage without contradiction.

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 well-structured with clear sections (Args, Returns, Examples, Error Handling) and front-loads the core purpose. Every sentence conveys necessary information without redundancy, making it appropriately concise for a tool with this complexity.

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?

Given the tool's complexity (5 params, TTL, transport independence, output formats) and lack of an output schema, the description covers all needed aspects: purpose, usage, params, return format, error handling, and examples. An agent can confidently invoke this tool correctly.

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%, so the schema already documents all parameters. The description repeats most parameter details and adds minor clarifications (e.g., TTL expiration behavior, key uniqueness), but does not significantly augment the schema. Baseline 3 is appropriate when schema handles the heavy lifting.

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 it persists key/value records to Semantic Memory for later retrieval via chaoscore_recall. It specifies the resource (Semantic Memory), the verb (persist), and distinguishes itself from the recall sibling by explicitly naming it as the retrieval counterpart.

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?

An explicit 'Examples' section provides a concrete use case ('Remember that the staging DB uses the Melbourne region') and a don't-use case ('You need to search existing memories -> use chaoscore_recall instead'). This directly instructs when to use versus when to use the sibling, leaving no ambiguity.

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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