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tinhien11

tdai-memory-mcp

by tinhien11

recall

Search past memory with natural language to find project context, prior work, and referenced details. Call before answering to retrieve relevant memories.

Instructions

Retrieve relevant past memory. Call this tool before you answer the user. Use it when the user references past work or when the task needs project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoThe search mode.hybrid
limitNoThe maximum number of results.
queryYesA natural language query. The tool uses this text for the BM25 search and the vector search.
offsetNoThe pagination offset. Use this to get the next page of results.
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.
max_tokensNoThe maximum number of tokens in the response. If the result exceeds this value, the tool truncates the text.
session_keyNoThe session key. The default is hash(cwd). Use this to recall memory from a different project.
Behavior3/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It indicates a non-destructive read operation via 'Retrieve' and adds a useful behavioral hint about calling it before answering. However, it does not detail potential side effects, authentication needs, or how results are shaped beyond what the schema already implies.

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 composed of three short, purposeful sentences: it states the core function, provides an invocation directive, and lists two use cases. There is no redundancy or fluff; each sentence earns its place.

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?

For a tool with 10 parameters, no output schema, and no annotations, this description is minimal. It covers primary use cases and timing but does not describe the return format, potential edge cases, or limitations. The detailed schema mitigates some gaps, yet a more complete description would be helpful for such a complex tool.

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 10 parameters clearly explained in the input schema. The description itself does not elaborate on any specific parameters, adding only generic context like 'past work' and 'project context' rather than clarifying parameters such as session_key or task_id. This meets the baseline without adding extra value.

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 begins with 'Retrieve relevant past memory,' which clearly specifies the action (retrieve) and resource (past memory). It distinguishes itself from sibling tools like capture and forget by focusing on retrieval rather than creation or deletion, and the phrase 'relevant' implies context-based recall.

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 provides explicit guidance on when to use: 'Call this tool before you answer the user' and 'Use it when the user references past work or when the task needs project context.' This gives clear context and conditions, though it does not explicitly state when not to use it or mention alternative tools such as search.

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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