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Glama

DDMarketer

by io.github.CodePhantom-1

Search validated SaaS gaps

search_gaps
Read-only

Search validated software opportunities by keyword. Each gap is a real, recurring user complaint scored for commercial intent (willingness to pay). Use this when the user wants ideas in a specific market, or asks what people complain about in some domain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax gaps to return (1-25, default 10).
queryYesKeywords describing the market or problem space, e.g. 'shopify accounting' or 'developer onboarding'.
categoryNoOptional exact category filter, e.g. 'E-commerce', 'DevTools'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
gapsYes
looseNoTrue when no gap matched all your terms and these are loosely related instead. Not validation.
totalYes
dossierUrlYes
upgradeUrlNoPresent only when the caller's plan does not include full dossiers: the page that unlocks them. Surface it when the user wants depth the teaser does not have.
attributionYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedOutput schema / properties / upgradeUrl
      Added value: +{
+  "description": "Present only when the caller's plan does not include full dossiers: the page that unlocks them. Surface it when the user wants depth the teaser does not have.",
+  "type": "string"
+}
  2. Changed2 schema fields changed
    • addedOutput schema / properties / gaps / items / properties / publicUrl
      Added value: +{
+  "description": "Public page for this gap, readable with no account: the complaint, the scores, and how it compares in its category. Offer this first.",
+  "type": "string"
+}
    • changedOutput schema / properties / gaps / items / properties / url / description
      Previous value: -"Link to give the user for this specific gap."New value: +"Link to this gap's full dossier. Requires a free account; anonymous visitors are redirected to signup and land back on THIS gap."
  3. Changed2 schema fields changed
    • addedOutput schema / properties / gaps / items / properties / category / description
      Added value: +"Broad product category, e.g. 'E-commerce' or 'DevTools'. Reusable as the category filter."
    • addedOutput schema / properties / gaps / items / properties / title / description
      Added value: +"The opportunity, phrased as what is missing."
  4. Changed1 schema field changed
    • addedOutput schema / properties / gaps / items / properties / url
      Added value: +{
+  "description": "Link to give the user for this specific gap.",
+  "type": "string"
+}
  5. Changed2 schema fields changed
    • removedOutput schema / properties / gaps / items / properties / trending
      Removed value: -{
-  "type": "boolean"
-}
    • changedOutput schema / properties / gaps / items / required
      Previous value: -[
-  "id",
-  "title",
-  "category",
-  "commercialIntent",
-  "confidence",
-  "trending"
-]New value: +[
+  "id",
+  "title",
+  "category",
+  "commercialIntent",
+  "confidence"
+]
  6. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already signal read-only and open-world behavior, so the bar is lower. The description adds meaningful context by explaining that results are 'real, recurring user complaint[s]' scored for commercial intent, which clarifies what 'validated' means. It doesn't cover edge cases like empty result sets, but safety is already carried by annotations.

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?

Three tight sentences with no filler: action plus resource first, data semantics second, usage trigger third. Every sentence earns its place and the key information is front-loaded.

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?

For a low-complexity search tool, everything needed to invoke it correctly is present: what results represent, the use trigger, and full parameter documentation in the schema. The output schema and annotations cover return values and safety, so no critical disclosure is missing; not naming siblings is a minor nicety rather than a gap.

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% for all three parameters, so the schema carries the full documentation burden. The description only reinforces the query keyword semantics without adding syntax, defaults, or format details beyond what the schema already provides.

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 first sentence names a specific verb (search) and resource (validated software opportunities/gaps), and the second sentence defines what a gap is. The 'by keyword' framing cleanly distinguishes it from siblings like get_top_gaps (top-list retrieval) and validate_idea (validation workflow).

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?

Explicitly states when to use it: 'when the user wants ideas in a specific market, or asks what people complain about in some domain.' It provides a clear trigger context but never names alternatives or exclusion cases, so it stops short of full when/when-not 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

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct role: browse top gaps, search gaps by keyword, retrieve a full dossier for a specific gap, and validate a new idea. The descriptions make the boundaries between list, search, detail, and evaluation obvious, so an agent should rarely misselect.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: get_dossier, get_top_gaps, search_gaps, validate_idea. The verb clearly signals the action and the noun identifies the resource, making the naming predictable.

Tool Count5/5

With four tools, the server is tightly scoped for market-gap discovery and validation. Each tool covers an essential part of the workflow without redundancy, and the count is comfortably within the ideal range.

Completeness5/5

The tool surface covers the main user journeys: finding trending opportunities, searching by market, drilling into one gap, and testing a custom idea. There are no obvious dead ends or missing operations for the server's stated purpose.

Resources