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What Taseli did

what_we_did
Read-onlyIdempotent

Changes Taseli made recently, in plain words, and what it is watching now; first, where each account stood before Taseli against the last 30 days ('since we started', with its honesty caveats). Useful for 'what did you do for me?'.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "what_we_did"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many events (default 10).
cursorNoFrom nextCursor of the previous answer.
languageNoAnswer language. The business's language by default.

Output Schema

NameRequiredDescriptionDefault
noteNoA plain note instead of data (nothing connected yet, not available here).
totalNoHow many there are in all.
eventsNo
watchingNo
truncatedNo
nextCursorNo
truncatedNoteNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already establish readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds some real context beyond that: results are rendered 'in plain words', include a baseline comparison window, and carry 'honesty caveats' about that baseline. It says nothing about pagination limits or how the watching-now section is scoped.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The lead clause 'Changes Taseli made recently, in plain words' is well front-loaded. What follows, however, is a dense, semicolon-chained sentence stuffed with parentheticals ('since we started', 'with its honesty caveats') that obscures rather than clarifies the returned content.

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

Completeness4/5

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

With an output schema present, annotations covering safety, and all three parameters documented in the schema, the description only needs to convey what the tool is for and roughly what comes back. It does that, though the account-baseline portion could be stated more plainly for a summary tool of this scope.

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 limit, cursor, and language are already documented in the schema, including the enum values and the default of 10. The description adds no meaning beyond that, which is the expected baseline when the schema does the work.

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 a specific resource: the changes Taseli made recently, what it is watching now, and a pre-Taseli vs. last-30-days baseline per account. That is concrete enough to separate it from siblings like list_decisions or explain_change, though no sibling is named explicitly and the phrase 'where each account stood before Taseli against the last 30 days' is hard to parse on first read.

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?

It gives one clear trigger, the user asking 'what did you do for me?', which implies a summary-of-activity use case. It does not say when to prefer explain_change, list_decisions, or get_results instead, and offers no exclusions, so the routing guidance is only implied.

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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