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Traceable

Upload Test Plan evidence

traceable_test_plan_evidence_upload

Upload a file as evidence on a Test Plan entry (or one of its test steps). Pass the file as base64 in content with its name. An image (PNG, JPEG, GIF, WebP, detected from the bytes, not the name) is shown inline in the Evidence column, exactly as an editor upload is. Any other file type is added to the project's Reference Library, referenced by this document, and attached as a file chip labelled in the document's citation format. At most 3 MB per file. Calling it twice uploads twice. The Test Plan row goes to review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowYesIdentify the Test Plan row by itemId or atOrder (pass one).
nameYesThe file name, e.g. "torque-trace.png" or "calibration.pdf"
stepNoA test step, numbered from 1; omit for the entry's own evidence
entryYesIdentify the entry by entryId or protocol (pass one).
contentYesThe file content, base64-encoded (a data: URL prefix is accepted)
documentIdYesThe document holding the Test Plan row

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: image types are detected from bytes not name and rendered inline, other files go to the Reference Library as a cited file chip, 3 MB per-file limit, and 'Calling it twice uploads twice' (consistent with idempotentHint=false). It also discloses the side effect that the Test Plan row goes to review, which no annotation conveys.

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

Conciseness5/5

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

Front-loads the core action, then packs the high-value behavioral facts (image detection, library fallback, size cap, non-idempotency, review status) into tight clauses. Every sentence carries information; nothing is filler.

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?

With no output schema, the description compensates by explaining the outcome (inline image vs. library reference and file chip) and the resulting state change. For a 6-param nested-schema mutation tool, the caller has enough to invoke it correctly.

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 the baseline is 3. The description reinforces that content is base64 with a name, but this largely repeats the schema's own 'base64-encoded' and naming docs, adding little new semantics about the nested row/entry selectors.

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 opens with a specific verb and resource: 'Upload a file as evidence on a Test Plan entry (or one of its test steps).' It is distinguishable from the read-oriented sibling traceable_test_plan_evidence because it states an upload action with targets (entry or step).

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?

The description implies when to use it (to attach evidence to a Test Plan entry/step) but never names an alternative or states conditions/exclusions versus siblings like traceable_test_plan_evidence or traceable_library_add_reference. Usage is inferable but not spelled out.

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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