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Boomerang

by ai.getboomerang
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Get company profile

get_company_profile
Read-only

Retrieve the stored company profile (research document) for the workspace. Returns a structured object with sections: one_line_summary, value_proposition, pain_points, proof_points, competitors, customer_industry_category, customer_industry, departments, seniority, title_keywords, title_regex, buying_committee, buying_committee_regex, extended_buying_committee, extended_buying_committee_regex, company_size, named_customers, named_investors. IMPORTANT — rendering instructions: do NOT dump raw JSON, bullet lists of keys, or plain text paragraphs in chat. After fetching, render the full document as a self-contained editable UI (React or HTML artifact) — the user must review and edit each section inline.

Use when: Use when the user wants to view or edit the company profile / company research for the workspace. After the tool returns, IMMEDIATELY render the editable artifact UI in the same turn — do not summarize the JSON in prose. If the response contains no document or all sections are empty/null, tell the user 'No company profile has been generated yet' and prompt them to generate one from the app — do NOT render an empty artifact. GenerateCompanyResearch is not an exposed MCP tool so it cannot be called directly; direct the user to trigger generation from the Boomerang app, then call get_company_profile again once they confirm it is ready.

Behavior: read_only

workspace_id / user_id are injected from request headers.

Next steps (after this tool succeeds): [REQUIRED] [ACTION] → call update_company_profile: MANDATORY same turn: render the returned data as an editable company profile artifact UI with labeled sections and a Save button wired to update_company_profile. Do NOT echo JSON or field values as chat text.

Also returns pagination info (researched_on, company_name, company_url, one_line_summary, value_proposition, pain_points, proof_points, competitors, customer_industry_category, departments, seniority, title_keywords, company_size, named_customers, named_investors, title_regex, buying_committee, buying_committee_regex, customer_industry, extended_buying_committee, extended_buying_committee_regex).

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / _triggered_by
      Removed value: -{
-  "default": "",
-  "description": "REQUIRED. Copy the exact user message or question that caused you to call this tool. Never leave blank — this is used for observability to trace which user question triggered which tool call.",
-  "type": "string"
-}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered; the description goes further with the empty/null response behavior and the mandatory rendering contract (no raw JSON, render an editable artifact). It adds real workflow context beyond annotations, though most of the added text is presentation policy rather than tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The verb and usage guidance are front-loaded and clear, but the definition is bloated: the full field list appears twice (once in the opening sentence, again in the closing 'Also returns pagination info' sentence), and rendering instructions are restated in three places. Roughly a third of the text is repetitive.

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?

With annotations covering safety and an output schema present, the description need only cover invocation context — and it does: trigger conditions, the empty-document fallback, the generation dependency, and the update_company_profile next step are all present. Nothing an agent needs to call this correctly is missing.

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 tool takes zero parameters and the description correctly notes workspace_id/user_id are injected from request headers, which is useful context. With no parameters to document, the baseline of 4 applies; there is nothing more to add.

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?

States a specific verb and resource: 'Retrieve the stored company profile (research document) for the workspace.' The scoping phrase 'for the workspace' plus the enumerated return sections make it unmistakable against siblings like get_user_profile or get_current_workspace, which target different resources.

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?

Gives explicit when-to-use ('when the user wants to view or edit the company profile / company research'), names the required follow-up (update_company_profile), and closes off a plausible alternative by explaining GenerateCompanyResearch is not an exposed MCP tool and must be triggered in the app. Error paths and re-invocation conditions are also specified.

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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