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add_reading

Apunta el valor de una métrica para un día. Queda ligado a la versión de su ficha.

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": {
      "project": "<project>",
      "metric": "<metric>",
      "value": "<value>",
      "on": "<on>"
    },
    "name": "add_reading"
  }
}

Input Schema

NameRequiredDescriptionDefault
onYesEl día (AAAA-MM-DD) o el mes (AAAA-MM) al que corresponde el valor. «Este mes» es el mes, no hoy.
noteNo
basisNomedido solo si hay datos detrás; lo que alguien cuenta es contado.
valueYes
metricYesm1 o su nombre.
projectYesEl proyecto (p1, p2…), de list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-idempotent, non-destructive mutation, so the safety profile is covered. The description adds a genuine trait beyond that: the reading is bound to the version of its sheet ('Queda ligado a la versión de su ficha'). It does not explain duplicate-entry behavior despite idempotentHint=false.

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 tight sentences with the core action front-loaded and the versioning caveat second. Nothing is padded, though the brevity edges into under-specification for a 6-parameter mutation.

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?

For a mutation with six parameters, two of them undocumented and no output schema, the description is thin. It omits what happens on error, repeated submissions, or invalid value formats, which an agent needs before writing data.

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 coverage is 67%, with good descriptions on on, basis, metric and project, but none on value and note. The description adds no parameter meaning at all, so the baseline 3 applies – it neither compensates for the gaps nor wastes effort restating the schema.

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?

States a specific verb+resource: recording a metric's value for a given day. The second sentence hints at versioning behavior. It does not, however, distinguish itself from siblings like define_metric or record_decision, so an agent must infer which add_* tool fits.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use or when-not-to-use guidance is given, and no alternative (e.g. define_metric for creating the metric itself) is named. The only prerequisite hint is in the schema ('de list_projects'), not the description.

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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