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tech-recall

tech-recall

by WItaZhang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

manage_card

Delete or restore a technology bookmark card using native user confirmation, without uninstalling any project dependencies.

Instructions

Delete or restore via native user confirmation. Does not uninstall any project dependencies.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "card_id": "<card_id>",
      "expected_revision": "<expected_revision>",
      "operation": "<operation>"
    },
    "name": "manage_card"
  }
}

Input Schema

NameRequiredDescriptionDefault
card_idYes
operationYes
expected_revisionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare destructiveHint=false, which the description makes coherent by pairing delete with restore (i.e. a reversible soft delete). It adds two useful behavioral facts beyond the annotations: a native user confirmation is triggered, and project dependencies are explicitly untouched. It still omits what happens to the card's data or links and whether restore is only available after a delete.

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?

Two short sentences, front-loaded with the operations, with no filler. The second sentence is slightly puzzling out of context but earns its place as a negative-scope disclosure.

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

Completeness2/5

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

An output schema and annotations cover return values and the safety profile, but for a mutation with an optimistic-concurrency parameter the definition leaves all parameter meaning and all failure behavior unaddressed. An agent could not tell from this text how to supply or recover from expected_revision.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for three required parameters, so the description carries the full burden, yet it never mentions card_id, the delete/restore operation enum, or expected_revision. The concurrency semantics of expected_revision (what a stale revision causes) are entirely undocumented anywhere.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names two concrete operations, delete and restore, on the resource identified by the tool name (card). That is enough for an agent to know the verb and resource, but it offers no differentiation from siblings such as confirm_card or prepare_card, which sit in the same workflow.

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?

'Via native user confirmation' implies the tool drives its own confirmation step, which is a usage hint, but there is no explicit when-to-use versus confirm_card/prepare_card and no statement of prerequisites or when not to call it. Usage is inferable rather than stated.

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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