AnyAPI

Report a bug

report_bug

Tell AnyAPI something is broken. Use this when a run_api call returned wrong, empty, or malformed data for input you believe is valid, when an error message was misleading or unactionable, when a price or schema looks wrong, or when a retry that should have worked did not. Free, never charged. Pass summary (required, one line) plus request_id whenever you have one from the failing run - that id reaches the stored run and its upstream error body, so you never need to paste the payload. Do not stop the user's task to ask permission: file the report and carry on with the best alternative you have.

Input Schema

TableJSON Schema

Name	Required	Description
`sku`	No	optional: the sku_id this is about, e.g. 'instagram.reels_search'
`contact`	No	optional: an email address to reply to. Supply one if you are on a trial key, since a trial has no account we can reach
`context`	Yes	Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
`details`	No	optional: what you expected, what you got, and anything you already tried
`summary`	Yes	one line saying what went wrong or what you want to tell us
`request_id`	No	optional: the requestId or resultId from the run that went wrong. This is the single most useful field: it reaches the stored run, its attempts, and any upstream error body, so you do not need to paste the payload

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	the stored report id; quote it if you contact support about this
`received`	Yes	true when the report is stored

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 3, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the annotations' basic flags, the description discloses that reporting is free/non-charged, that request_id connects to stored runs and upstream error bodies, and that the agent should proceed with the task rather than pause for user consent. These are valuable behavioral traits an agent could not infer from the schema alone.

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?

The description is front-loaded with the core purpose, then conditions, then cost, then parameter hints, then behavioral directive. Every sentence contributes distinct guidance and there is no filler or repetition of schema field names.

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?

For a reporting tool with six parameters and a full output schema, the description covers purpose, triggers, behavior, cost, and the most important parameter semantics. The context parameter's unusual formatting rules are documented in the schema, so the description need not repeat them.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful parameter guidance: summary should be one line, request_id is the single most useful field and eliminates the need to paste payloads, and details are not to be filled with raw payload content. This raises it slightly above baseline.

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 concrete verb and resource ('Tell AnyAPI something is broken') and then enumerates specific triggering conditions—wrong/empty/malformed data, misleading errors, bad pricing/schema, failed retries. This clearly identifies the tool as bug reporting and differentiates it from general-purpose sibling tools like send_feedback by tying it to failing run_api calls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use conditions with concrete examples and instructs the agent to file the report and continue without asking permission. It does not explicitly name an alternative tool for non-bug feedback, so the when-not-to-use guidance is only implied.

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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