Who buys what you sell: count the decision-makers that fit, with real examples and buying signals.
Scored across 1 tool
With a single tool there is no possibility of misselection; estimate_audience has one clearly stated purpose (sizing a market and surfacing example buyers). No overlapping or competing tools exist.
The lone name follows a clean snake_case verb_noun convention (estimate_audience) that is self-descriptive and predictable. Nothing else exists to conflict with it.
One tool is thin even for a narrow domain; the description hints at a rich output (roles, counts, examples, signals, link) but everything is bundled into a single heavyweight call taking 30-90 seconds. A small companion set (e.g. refine filters, retrieve full list) would be more ergonomic.
The core job of identifying and sizing an audience is covered in one call, but the surface is a dead end afterward: no way to page through more examples, save or re-run a search, filter results, or export the list programmatically. Agents can work around this only via the returned Deberli link.
Estimates how many decision-makers fit a business's offer.
Returns the roles, places, industries and company sizes searched; the total count; five real example people (names blurred, companies unnamed) with a fit score; the buying signals Deberli tracks for that market; and a link that opens the full list in Deberli. Use it when the user asks who to sell to, how big their market is, or where to find customers or leads. Read-only. Takes 30-90 seconds.
| Name | Required | Description | Default |
|---|---|---|---|
| brief | No | One or two sentences: what the business sells and to whom. Give this or website. | |
| market | No | Country or region the business sells in, e.g. United Kingdom. Without it the count covers every country. | |
| website | No | The business's website, e.g. acme.com. Give this or brief. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=false, so 'Read-only' merely repeats structured data. The genuinely additive disclosures are the 30-90 second runtime and the preview of what the response contains (counts, example people, buying signals), which help an agent set expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded in the first sentence, with usage and behavioral notes following. The middle sentence enumerating return contents is fairly long and partly duplicates the output schema, but overall it is well-organized and free of filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the description needn't detail return values, and annotations cover the safety profile. Combined with explicit usage triggers and latency expectations, nothing needed to invoke this tool correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already explains brief, market, and website including the 'give this or X' alternatives. The description adds no syntax or format detail beyond that, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Estimates how many decision-makers fit a business's offer'), which is unambiguous and self-contained. With no siblings, no differentiation is needed, and the purpose is clear on its own.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly names the triggering user intents: 'who to sell to, how big their market is, or where to find customers or leads.' No alternatives exist to route against, so this fully covers the guidance an agent needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Add one secure layer between your agents and this server.
