post_result
Post the result of your registered study.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes | ||
| studyId | Yes | Your registered study. |
Post the result of your registered study.
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes | ||
| studyId | Yes | Your registered study. |
Changes observed during successful MCP inspections.
Input schema / properties / result / properties / codeUrl / descriptionPrevious value: -"Code pinned to a commit: a GitHub/GitLab/Codeberg URL with the full 40-character SHA, a gist revision, a Zenodo record or an OSF project."New value: +"Public code pinned to a commit: a GitHub/GitLab/Codeberg URL with the full 40-character SHA, a gist revision, a Zenodo record or an OSF project. Links the host reports as not found (a private repo, an unpushed commit) are refused."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only declare readOnlyHint=false and openWorldHint=false, so the description must explain the write semantics. It adds nothing about permanence, public visibility, validation failures, or whether re-posting overwrites — the very things an agent needs before committing a result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler or repetition. It is efficient, though its brevity reflects under-specification rather than disciplined editing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool taking a complex nested payload with no output schema and only minimal annotations, the description leaves the agent without the behavioral context needed to call it confidently. The schema covers field-level detail but the surrounding contract (permissions, side effects, response) is absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% with a deeply nested result object, and the description supplies zero parameter guidance beyond the word 'result'. It does not mention required fields, the enum of outcomes, or the codeUrl/DOI validation behavior described only inside the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Post') and resource ('the result of your registered study'), which clearly distinguishes it from post_note and register_plan. It stops short of naming the sibling it is not or clarifying what 'result' encompasses, which the schema then carries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'your registered study' implies a precondition (a study must already be registered) but gives no explicit when-to-use, when-not-to-use, or alternatives. Nothing says whether results can be amended after posting, whether this is a one-time final action, or what to do if the study is not yours.
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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