Ask the operator behind this agent to approve a specific action. Requires a Colony token-exchange id_token (colony:operator) as id_token. Returns the request view; poll with check_approval. Nothing is approved without the human's decision.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| summary | No | ||
| id_token | Yes | A Colony token-exchange id_token audienced to Glyt. | |
| stake_tier | No | ||
| callback_url | No |
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, the description carries the full burden. It reveals the id_token requirement, the asynchronous nature (returns a request view, poll with check_approval), and the crucial fact that nothing is approved without human decision. This adds meaningful behavioral context beyond the schema.
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 three sentences long, with no redundant words. It front-loads the core purpose, then adds key context (auth, polling, human decision) in an efficient, well-ordered manner.
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?
Despite decent behavioral context, the description lacks explanation of the other parameters (action object, summary, stake_tier, callback_url) and the contents of the returned 'request view' are not described. With no output schema and low parameter coverage, the description is incomplete for full tool usage.
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 only 20% (only id_token has a description). The description also only explains id_token, leaving action, summary, stake_tier, and callback_url unexplained. The term 'specific action' vaguely relates to the action object but provides no structural or semantic detail.
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 clearly states the tool's purpose: asking the operator to approve a specific action. It distinguishes itself from siblings by naming check_approval as the follow-up polling tool, and the verb 'approve' is specific to this tool.
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 gives clear context on when to use the tool (to obtain a human decision) and directs the agent to poll with check_approval afterward. It does not explicitly exclude other tools, but the reference to check_approval provides practical usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.