Distill completed tasks into knowledge points stored in vector memory, converting title, description, and results into searchable context for future tasks.
任务完成自动沉淀：把一条已完成/已有结果的任务(标题+描述+结果)提炼成知识点写进向量记忆(memory_add)。供后续任务 memory_search 复用。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | ||
| scope | No | ||
| source | No | ||
| task_id | Yes | ||
| category | No | 记忆 category，默认 global:bridge |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the main side effect (writing to memory) but does not explain whether the original task is modified, whether duplicates are avoided, what permissions are needed, or what happens on failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no filler. The core action is front-loaded and the downstream benefit is stated efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there are no annotations, no output schema, and five parameters, the description is too thin to fully support correct invocation. It does not mention return values, side effects on task state, or parameter roles beyond the high-level purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 20%, so the description should compensate for the undocumented cwd, scope, source, and task_id parameters. It only implies that task_id refers to a completed task and mentions memory_add, without explaining how each parameter is used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action: distilling a completed or result-bearing task into a knowledge point and writing it to vector memory via memory_add. It distinguishes itself from generic memory tools by tying the behavior to task completion, though it does not explicitly name sibling alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear context for when to use the tool: after a task is completed or already has a result, to enable later memory_search reuse. It lacks explicit exclusions or comparisons to task_complete or memory_add, but the intended trigger is reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.