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Analook — Competitor Intelligence

by io.github.Gingiris-1031

get_report_markdown

Fetch the competitor analysis report as human-readable Markdown.

Suitable for piping into agents that prefer text over structured JSON,
or for direct display to end users.

Args:
    job_id: ID from analyze_competitor(); status must be 'completed'

Returns:
    {markdown: str} or {error: str}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
contextYesExplain 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."
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It specifies the return format ({markdown: str} or {error: str}) and the precondition of job status being 'completed', which is useful. However, it does not elaborate on what happens if the status is not completed, potential error details, or any authentication/rate-limit considerations, leaving some behavioral ambiguity.

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 concise and well-structured. It opens with the primary purpose, follows with usage suitability, and then presents the Args and Returns clearly. Every sentence provides essential information without unnecessary elaboration, making it efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description covers the essential aspects: what the tool does, when to use it, the required input, and the return type. It also mentions the status prerequisite. However, it lacks explicit details about error scenarios and how this tool relates to the sibling get_report, though the mention of 'structured JSON' hints at that. Given the simplicity of the tool, the description is nearly complete.

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?

The description adds meaning beyond the schema by documenting the job_id parameter: 'ID from analyze_competitor(); status must be completed.' This compensates for the schema's lack of a description for job_id. The context and conversation_id parameters are already thoroughly described in the schema, so the description does not need to repeat them. Overall, the description fills the gap in parameter understanding.

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 clearly states the tool's function with a specific verb and resource: 'Fetch the competitor analysis report as human-readable Markdown.' It distinguishes itself from the sibling get_report by emphasizing the Markdown format, and the additional note about piping into agents that prefer text further differentiates its use case.

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?

The description provides clear guidance on when to use the tool: 'Suitable for piping into agents that prefer text over structured JSON, or for direct display to end users.' It also includes a prerequisite that job_id must come from analyze_competitor() and status must be 'completed'. While it does not explicitly name alternative tools, the suitability note implies when it should be chosen over structured JSON retrieval.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Analook — Competitor Intelligence toolsInspect
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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource+action: analyze/run create jobs, get_report/get_report_markdown/get_growth_audit retrieve different output formats, status polling is separate, and the two listing tools (public vs personal) are clearly differentiated by name and description.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (analyze_competitor, browse_public_reports, get_report, run_growth_audit). The get_* verbs are consistently used for retrieval, and list_* for list operations.

Tool Count5/5

8 tools is well-scoped for a competitor intelligence API: two job submission types (competitor analysis, growth audit), retrieval in both JSON and Markdown, status polling, and listing/browsing. Each tool serves a distinct purpose with no redundancy.

Completeness4/5

The core lifecycle (submit → poll → fetch) is fully covered for both analysis types, with additional reporting and discovery features. Minor gaps exist (e.g., no cancel operation, no direct full-text retrieval of public reports), but they don't block primary workflows.

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