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Analook — Competitor Intelligence

by io.github.Gingiris

get_growth_audit

Fetch a Growth Audit's three reports (Executive Summary, Diagnosis, Action Plan) as Markdown.

Args:
    job_id: ID from run_growth_audit() (starts with 'ga-')

Returns:
    {status, reports: {executive_summary, diagnosis_report, action_plan}}
    while running, only {status, progress} is returned.

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

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that while the audit is running, only {status, progress} is returned, which is a key dynamic behavior. It also specifies the exact return structure with report keys, adding valuable 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured with Args and Returns sections. It uses only two sentences plus the structured details, with no wasted words. The main purpose is front-loaded in the first sentence.

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?

The description explains the return shape, the Markdown format, the progressive return behavior, and the source of job_id. It does not mention error handling or invalid job_id conditions, but for a simple fetch tool with no output schema, this is fairly complete. Sibling tools like get_report_status are not referenced, but the job_id linkage covers the primary usage context.

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 provides critical semantics for job_id: it is the ID from run_growth_audit() and starts with 'ga-'. The schema only defines job_id as a type, so this fills a gap. The context and conversation_id parameters have schema descriptions, so overall parameter understanding is strong.

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 states a specific verb ('Fetch') and a specific resource ('a Growth Audit's three reports') in Markdown format. This clearly distinguishes the tool from siblings like get_report or get_report_markdown, which might fetch individual reports or other markdown documents.

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 states that job_id comes from run_growth_audit(), clearly implying this tool should be used after launching a growth audit. It does not explicitly state when not to use it or name alternative tools, but the job_id dependency gives strong contextual guidance.

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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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clear distinct purposes: job submission, status polling, report retrieval, and listing are separated. Some potential confusion exists between get_report/get_report_markdown (same content, different format) and get_report_status/get_growth_audit (both return status for different job types), but descriptions clarify these boundaries.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with lowercase and underscores: analyze_competitor, browse_public_reports, get_growth_audit, get_report, get_report_markdown, get_report_status, list_my_reports, run_growth_audit. No mixed conventions or camelCase.

Tool Count5/5

8 tools is well-scoped for a competitor intelligence server, covering two distinct workflows (competitor analysis and growth audit) plus report browsing and retrieval. Each tool serves a clear purpose without feeling bloated or skeletal.

Completeness4/5

The core lifecycle is covered: submit analysis, poll status, fetch report in JSON/Markdown, list personal reports, and browse public reports. Minor gaps remain, such as no way to list past growth audits or cancel/delete jobs, but these are not critical for the primary use case.

Resources