Skip to main content
Glama

Analyze company opportunity

analyze_company

Use when a specific company and website are known. Returns explainable FIT / NEED / NOW opportunity intelligence and saves the analysis as an AGENT / API history source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNoOptional state, province, canton or regional area of the company.
addressNoOptional postal or street address used to disambiguate the company.
countryNoCompany country or market. Use DACH when the exact DACH country is not yet known.DACH
websiteYesCompany website URL, preferably including https:// when known.
districtNoOptional district, county or local administrative area of the company.
industryNoOptional company industry or business category used to improve analysis context.
languageNoHuman-readable analysis output language: de, en, es or fr.en
company_nameYesOfficial or commonly used company name to analyze.
google_place_idNoOptional Google Place ID when already known for more precise company matching.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / language
      Added value: +{
      +  "default": "en",
      +  "description": "Human-readable analysis output language: de, en, es or fr.",
      +  "title": "Language",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

The description discloses a meaningful side effect: 'saves the analysis as an AGENT / API history source.' This goes beyond the annotations, which only indicate readOnlyHint=false, openWorldHint=true, and idempotentHint=false. It also states the nature of the returned intelligence. It doesn't cover cost/credit consumption, but the annotations already signal non-read-only behavior.

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 a single, front-loaded sentence that conveys the trigger condition, the return value, and the side effect with no filler. Every clause earns its place.

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 9 parameters and a full output schema, the description gives the essential context: what triggers it, what it returns, and that it persists history. It could additionally mention whether credit consumption applies, but the schema and output schema carry much of the remaining burden.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema already documents all parameters in detail. The description adds the contextual requirement that company_name and website be known, but does not explain parameter formats or relationships beyond what the schema provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('analyze') and resource (a specific company with known website) and clarifies the deliverable ('FIT / NEED / NOW opportunity intelligence'). It differentiates from broad alternatives like discover_leads and find_opportunities by requiring a known company and website, though it does not name sibling tools explicitly.

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 explicitly opens with 'Use when a specific company and website are known,' which gives a clear trigger condition. It does not mention exclusions or alternative tools by name, but the condition is specific enough to guide tool selection among the siblings.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.4/5.0
Disambiguation2/5

Several tools overlap or duplicate: run_sales_mission intentionally duplicates check_sales_mission_status and get_sales_mission_result, and there are multiple capability/routing tools (get_capabilities, match_alpinelead_capability, get_alpinelead_recommendation_packet, recommend_next_tool) with similar purposes. Blank descriptions for several nexus_* tools make their boundaries even harder for an agent to determine.

Naming Consistency2/5

All names use snake_case, but there is no consistent verb_noun pattern. The set mixes prefixed families (agentpub_*, nexus_*, predictive_*_info), noun-only names (winning_pattern, learning_engine), reversed noun_verb names (radar_check, hunter_run), and get/check/run/status variants for closely related operations.

Tool Count1/5

56 tools is far beyond a well-scoped server surface. Many are one-off info, status, or diagnostic tools that could be consolidated into parameterized tools. This places an excessive routing burden on the agent and dilutes the core sales workflow.

Completeness3/5

The core lead-to-CRM workflow is fairly complete: discovery, analysis, qualification, sales kit generation, HubSpot push, and learning/feedback loops are covered. However, there are notable gaps such as no way to list or retrieve saved analyses, no explicit stop/cancel for Hunter or Sales Mission runs, and no update/cancel operations for Nexus tasks.

Resources