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Analook — Competitor Intelligence

by io.github.Gingiris-1031

run_growth_audit

Run a full Growth Audit — three linked strategic reports for a product.

Unlike analyze_competitor (a single 15-signal intelligence snapshot), a
Growth Audit produces an Executive Summary + a Diagnosis Report + a 30-day
Action Plan, grounded in real channel/tactic playbooks. Best for 'how do I
grow THIS product' rather than 'what is this competitor doing'.

Takes ~4-6 minutes. Requires authentication and deducts 10 credits. Poll
with get_growth_audit(job_id) until status='completed'.

Args:
    url: Product website URL to audit
    product_name: Optional product name override (defaults to domain)
    lang: Report language, 'en' (default) or 'zh'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
langNo
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."
product_nameNo
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

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the operation takes ~4-6 minutes, requires authentication, deducts 10 credits, and is async (poll with get_growth_audit). These are precisely the non-obvious behaviors an agent needs to know.

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 well-structured: a one-line summary, a comparison sentence, operational details (time, auth, credits, polling), and a compact Args list. Every sentence serves a purpose, and no content is redundant or filler. It is appropriately detailed for a complex async tool.

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

Completeness3/5

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

The description covers the high-level business logic well, but it omits two parameters (context and conversation_id) from its Args section. The required context parameter is entirely absent from the description, which could mislead an agent into thinking only url is required. The schema fills this gap, but the description itself is incomplete for such a complex tool.

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 description coverage is 40% (low), so the description must compensate. It adds meaningful semantics for url, product_name, and lang (e.g., product_name defaults to domain, lang supports 'en'/'zh'). However, it omits the required context and conversation_id parameters, which the schema already describes. The description adds value for most business params but is incomplete in its Args list.

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: 'Run a full Growth Audit — three linked strategic reports for a product.' It explicitly lists the outputs (Executive Summary + Diagnosis Report + 30-day Action Plan) and distinguishes it from the sibling analyze_competitor, so the agent knows exactly what this tool does and how it differs.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool versus alternatives: 'Unlike analyze_competitor... Best for how do I grow THIS product rather than what is this competitor doing.' It also instructs the agent to poll with get_growth_audit(job_id) after running, which is a key usage step.

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

A4.4/5.0
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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