Agency Opportunity Radar

by AlanFNL

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clear, distinct purpose without overlap. Profile tools manage the agency profile, opportunity discovery and audit are separated, and post-audit tools (compare, history, outcome, export) serve unique functions.
Naming Consistency5/5
All tools follow a consistent 'domain_action' pattern using snake_case, with 'agency_profile_' or 'opportunity_' prefixes and clear verbs (set, get, discover, audit, compare, search_history, record_outcome, export).
Tool Count5/5
8 tools align well with the server's purpose. Each tool covers a necessary step in the workflow from profile setup to discovery, audit, comparison, history, outcome recording, and export without being excessive or insufficient.
Completeness4/5
The tool set covers the main workflow comprehensively, but lacks explicit update/delete tools for audits or opportunities. There is also no direct listing of all opportunities, though search_history with filters partially addresses this.
Average 3.4/5 across 8 of 8 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds that it retrieves historical data with transparent filters, providing some context but not going beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence but lacks structure. It front-loads the verb 'Retrieves' effectively, but could be improved with more detail on parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no schema descriptions, the description is too brief. It does not cover key aspects like time range filtering or status options, leaving significant gaps for such a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, it only mentions 'transparent filters' without explaining any of the 7 parameters, adding no semantic value.
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 clearly states the tool retrieves persisted searches, audit snapshots, and outcomes using transparent filters. It specifies the action and resources but does not explicitly distinguish it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks any context about appropriate use cases or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, idempotent operation. The description adds that the comparison is 'compact' and 'consistently shaped' and that it does not generate sales copy, but this is minimal additional behavioral context.
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, clear, and concise sentence with no unnecessary words. It front-loads the core purpose and is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the description fails to explain the input parameters, which have no descriptions in the schema. With sibling tools that have similar inputs, more context is needed to ensure correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions in the schema. The description does not mention any parameters or explain what opportunityIds or serviceIds represent. This is a critical gap for effective tool use.
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 clearly states the tool returns a comparison of saved audit snapshots, with a specific verb 'returns' and resource 'saved audit snapshots'. It does not explicitly differentiate from siblings like opportunity_discover or opportunity_audit, but the operation is distinct enough to be understood.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like opportunity_discover or opportunity_audit. No exclusions or context for use are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behaviors: the audit is bounded and robots-aware, returns detailed results, and never submits forms. This adds value beyond annotations (which don't mention these specifics). However, it could further detail what 'bounded' means (e.g., limits on pages or depth).
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?
Two sentences, no wasted words. The 'never submits forms' adds a key safety note efficiently. Front-loaded with the main action and return types.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the description lacks essential input parameter details and does not clarify scope ('bounded') or prerequisites. For a tool with 6 parameters and no schema descriptions, more completeness is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameter purposes. It fails to mention any of the 6 parameters (url, depth, refresh, maxPages, serviceIds, candidateId), leaving the agent without guidance on how to invoke the tool.
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 clearly states it runs a bounded, robots-aware public website audit and lists specific return types (observations, signals, failures, score reasons). The verb 'audit' and resource 'public website opportunity' are specific, but it does not explicitly differentiate from sibling tools like opportunity_discover.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context such as needing an existing opportunity ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds that it 'creates or replaces', which aligns with destructive. However, it does not disclose additional behavioral traits such as irreversible changes, required permissions, or performance impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, achieving conciseness. However, it lacks structure such as bullet points or sections; a slightly more structured format could improve scannability without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters (including complex nested services), no parameter descriptions, and a minimal description, the contextual completeness is low. The agent lacks guidance on what each field means or how to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning no parameter descriptions exist in the schema. The description provides no explanation of parameters (name, services, notes, targetMarkets, etc.). The agent receives no semantic guidance beyond the schema's type constraints.
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 verb 'creates or replaces' and the resource 'local agency profile', with a specific purpose 'used for fit and doability scoring'. This distinguishes it from sibling tools like agency_profile_get (retrieval) and opportunity_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for setting the agency profile but does not explicitly state when to use this tool versus alternatives (e.g., agency_profile_get) or when not to use it. No usage context, prerequisites, or side effects are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that files are never overwritten, which is a key safety trait, but does not explain behavior when a file already exists, permissions needed, or return value (though output schema exists).
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?
Two sentences, front-loaded with the primary action, no redundant text.
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?
With 3 parameters, no annotations, and an output schema, the description covers core purpose and a key constraint (no overwrite) but omits details on error handling, file naming conflicts, and required permissions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; the description adds minimal context (JSON/CSV format, export directory) but does not describe individual parameters like opportunityIds or filename semantics.
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 writes selected opportunities as JSON or CSV to a configured directory, distinguishing it from sibling tools like discovery, audit, and comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when or when not to use the tool versus alternatives; usage is implied by the tool name and purpose but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by mentioning normalization and the Google Places provider. It also states the tool does not deeply audit. No contradiction with annotations. However, it does not clarify whether the tool creates records (given readOnlyHint=false), which would be useful.
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 20-word sentence that immediately conveys the core action and constraints. No wasted words; front-loaded with the main verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count and lack of schema descriptions, the description is too brief. It does not explain the purpose among siblings beyond the audit comment, nor does it cover parameter usage or result behavior. The output schema exists but does not compensate for missing parameter context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description only explains 'websites' (explicit URLs) and 'provider' (Google Places), leaving 'query', 'location', 'limit', and 'serviceIds' undocumented. This is insufficient for a 6-parameter tool, even considering the output schema.
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 it 'finds and normalizes public business websites', specifying the verb and resource. It distinguishes from sibling 'opportunity_audit' by explicitly noting it does not deeply audit, making the purpose well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering candidates via URLs or Google Places, but does not provide explicit guidance on when to use versus alternatives or when not to use it. The 'not deeply audit' hint is helpful but insufficient for clear usage criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a write operation (readOnlyHint=false) and non-destructive (destructiveHint=false). The description adds clarity by confirming no external system changes, enhancing transparency beyond 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?
The description is two sentences, front-loaded with purpose and followed by side-effect clarification. Every word adds value.
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?
Given 6 parameters and the presence of an output schema, the description covers the overall operation but lacks parameter-level details needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should explain parameter meanings. It only provides high-level context without detailing required fields like status or optional ones like value and currency.
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 appends a human-reported outcome to an audited opportunity, using a specific verb and resource. This distinguishes it from sibling tools like opportunity_discover or opportunity_audit.
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 implies when to use (recording a manual outcome) and states it does not contact external systems, but does not explicitly list alternatives or when-not-to-use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only and idempotent. The description adds minimal context about being 'local' and for 'checking assumptions,' which is useful but does not significantly expand beyond what the annotations provide.
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 sentence, 13 words, with no wasted words. It front-loads the action ('Returns') and purpose.
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 tool with no parameters and an existing output schema, the description sufficiently communicates purpose and behavior. It is complete for the intended use.
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?
There are no parameters, so schema coverage is 100%. The description adds no parameter information, but the baseline score of 3 applies.
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 returns the current local agency profile, with a specific use case (checking assumptions before research). The name and title align, and it is distinguishable from sibling tools like agency_profile_set.
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 implies usage before research to verify assumptions, providing clear context. However, it does not explicitly state when not to use this tool or mention alternatives among siblings.
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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