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Glazecalc

by com.glazecalcapp
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Add readings to one of my firing logs

add_firing_rows
Destructive

Adds rows to the end of one of your firing logs (an id from list_firings), in the log's own columns (get_firing gives them): the readings dictated during a firing. The rows already there stay as they are, and the log as it was is kept as an earlier version. At most 500 rows a log. Save only what the person said and agreed to; never fill in an amount, temperature or analysis they did not give. Needs an access token that can read and change your records.

Input Schema

NameRequiredDescriptionDefault
idYesThe firing log, from list_firings.
revNoThe log’s rev as you last read it. When given, the rows are added only if the log has not changed since; otherwise nothing is changed. Left out, they are always added.
rowsYesThe new readings, in the log’s own columns (get_firing gives them), each row a cell for each column.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / rev
      Added value: +{
+  "description": "The log’s rev as you last read it. When given, the rows are added only if the log has not changed since; otherwise nothing is changed. Left out, they are always added.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, it discloses append-only semantics, preservation of existing rows, version retention, a 500-row cap, data-fidelity constraints, and the access-token requirement. These are specific behavioral and safety details that the annotations alone do not provide.

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?

The purpose is front-loaded and the sentences mostly earn their place by covering scope, versioning, limits, data fidelity, and auth. However, the first sentence is dense with parentheticals and the fragment 'At most 500 rows a log' slightly weakens flow.

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

Completeness5/5

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

For a three-parameter mutation with no output schema, the description supplies enough: it explains what is added, how existing data is treated, limits, versioning behavior, and auth needs. The schema covers the conditional rev semantics, so nothing critical is missing.

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 100%, so the schema already documents id, rev, and rows. The description reinforces id sourcing and row layout but does not add meaning for rev or otherwise go beyond the schema descriptions.

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 states a specific verb and resource: it adds rows to the end of a named firing log, with the id sourced from list_firings. It also clarifies that this is for readings dictated during a firing, distinguishing it from log creation or retrieval siblings.

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?

It gives clear context for use: you need an id from list_firings and columns from get_firing, and the rows are the readings during a firing. It does not explicitly say when to choose create_firing_log instead, or name other alternatives, so it misses full when-not guidance.

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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