Check your Disco account status.
Returns current plan, available credits (subscription + purchased), and
payment method status. Use this to verify you have sufficient credits
before running a private analysis.
Args:
api_key: Disco API key (disco_...). Optional if DISCOVERY_API_KEY env var is set.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds useful context about what is returned (plan, credits, payment method status) but does not cover potential errors or edge cases. Given the annotation coverage, a score of 3 is appropriate.
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 concise and well-structured: a one-line purpose, a brief explanation of return values, a usage scenario, and an Args note. Every sentence contributes without redundancy, making it easy to scan.
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?
Given the simple single-parameter tool, the readOnly annotation, and the presence of an output schema, the description covers the essential context: purpose, usage scenario, and parameter behavior. It does not mention prerequisites like having an account, but the context signals suggest this is not critical for selection.
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?
The only parameter, api_key, is explained in the Args section: 'Disco API key (disco_...)'. This adds format details and the env var fallback, which are not present in the schema. The schema only gives a type and default, so the description meaningfully compensates for the 0% schema coverage.
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 opens with 'Check your Disco account status', which is a specific verb and resource. It lists the returned fields (plan, credits, payment method status), making the purpose clear. It does not explicitly distinguish from the sibling 'discovery_status', but the focus on account information is distinct.
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 an explicit usage scenario: 'Use this to verify you have sufficient credits before running a private analysis.' This tells the agent when to invoke the tool. It does not mention alternatives or when not to use it, but the guidance is more than implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation (account, payment, analysis, plans, login flows, etc.) with no overlap. Even paired tools like signup/login and their verify counterparts are clearly differentiated.
All tools follow a consistent 'discovery_' prefix + verb_noun pattern (e.g., discovery_add_payment_method, discovery_get_results). No mixed conventions or vague names.
14 tools cover account management, analysis pipeline, and billing without unnecessary redundancy. The scope is well-matched to the server's purpose.
The tool set covers the full user journey from signup and payment to running analyses and retrieving results. Minor gaps exist (e.g., no explicit cancellation of subscriptions), but the core workflow is fully supported.