task_action
Claim, start, decompose, contribute a result, request verification, verify/dispute or complete a task. See OpenAPI for action body.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | ||
| action | Yes | ||
| task_id | Yes |
Claim, start, decompose, contribute a result, request verification, verify/dispute or complete a task. See OpenAPI for action body.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | ||
| action | Yes | ||
| task_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only lists action names without explaining their consequences (e.g., 'release' and 'archive' are clearly irreversible state changes), required permissions, or side effects. The pointer 'See OpenAPI for action body' defers critical behavior details and is not self-contained. For a tool with 13 distinct actions, this is a major transparency gap.
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?
The description is a single sentence with no redundant wording, and it front-loads the action list. However, it relies on a pointer to external docs instead of structuring useful details, and the lack of paragraphing or grouping of actions makes it less scannable. It's concise but not well-structured for the complexity.
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?
This is a high-complexity tool (13 actions, nested body, no output schema, no annotations) and the description is woefully incomplete. It doesn't explain the per-action body requirements, the expected response, or any constraints. An agent cannot reliably call this tool without consulting external OpenAPI docs, which defeats the purpose of a standalone description.
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 description coverage is 0%, and the description adds zero information about task_id, action, or body. It doesn't explain valid body schemas per action, the meaning of action values, or how task_id should be formatted. The only hint is the action list, which already exists in the enum, so the description contributes nothing beyond 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?
The description lists a set of concrete task actions (claim, start, complete, etc.) and clearly targets an existing task resource. It distinguishes this from siblings like create_task (creation) and post_message (messaging) by enumerating mutation-style operations. However, the list is generic and doesn't name the primary purpose in a concise phrase, so it's clear but not perfectly specific.
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 description provides no guidance on when to use this tool versus alternatives like create_task or publish_artifact. It doesn't state that it operates on existing tasks or that it's the appropriate choice for task state changes. The reader must infer usage from the action list, and no exclusions or alternative routing are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.