get_intelGet one development with its sources and context.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Intel ID | |
| activity | No | Activity rows to include: all (default), source observations only, or none |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / properties / data / properties / activity / items / additionalPropertiesAdded value: +falseOutput schema / properties / data / properties / activity / items / oneOfRemoved value: -[
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-]Output schema / properties / data / properties / activity / items / propertiesAdded value: +{
+ "action": {
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+}Output schema / properties / data / properties / activity / items / requiredAdded value: +[
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+]Output schema / properties / data / properties / activity / items / typeAdded value: +"object"Input schema / properties / activity / descriptionAdded value: +"Activity rows to include: all (default), source observations only, or none"Input schema / properties / id / descriptionPrevious value: -"Intel id"New value: +"Intel ID"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true (safe read) and destructiveHint=false. The description adds context about returning sources and activity details, which is valuable beyond annotations. It does not contradict annotations. However, it could further clarify pagination behavior or depth of context.
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?
The description is a single, concise sentence that effectively communicates the tool's purpose without unnecessary words. Every part contributes to understanding what the tool does.
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?
Given the schema covers both parameters and output schema is present (reducing need to explain return values), the description is fairly complete. It states the tool retrieves one development with sources and context. Slight room for improvement: noting that the output schema provides the structure, but overall good.
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%, so the schema already documents both parameters (id and activity). The description does not add extra meaning beyond 'get one development with its sources and context.' Baseline 3 is appropriate since schema handles param documentation.
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?
The description clearly states it retrieves a single development along with its sources and context. This is a specific verb (get) applied to a distinct resource (intel/development), and it differentiates from siblings like get_project or get_topic which retrieve different entities.
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?
The description implies use when needing a development's full details including sources and context. While it doesn't explicitly state when not to use it or name alternatives, the sibling list suggests other tools for different entity types, providing implicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct entity or action: single vs. list (get vs. list), intel vs. project vs. topic vs. report vs. cluster vs. vocabulary vs. credential check. No two tools have overlapping purposes; the descriptions clearly differentiate them.
Uses a consistent pattern: get_ for singular retrieval, list_ for plural searches/listing. Only 'me' deviates, but it's a standard name for credential checks. The pattern is predictable and easy to follow.
12 tools cover a focused domain (crypto intelligence) without unnecessary bloat. Each tool earns its place: core entities (projects, topics, intel), plus series, reports, vocabulary, clusters, and auth check. The count feels well-scoped.
The server provides a complete read surface for its domain: listing, searching, getting details, historical series, reports, and filter metadata. No obvious gaps for consuming intelligence (CRUD not expected in a read-only API).