Full markdown text of one published research document, by slug (see research_journal for the list). Verbatim internal writing; credential identifiers redacted.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | slug from research_journal, e.g. 2026-08-01_c2_null_calibration_memo |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses that content is verbatim internal writing, that credential identifiers are redacted, and that the output is full markdown text. It could add detail about behavior on invalid slugs or availability, but the key behavioral traits are covered.
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?
Two concise sentences with no filler. The first sentence front-loads the action and the source of the identifier, and the second clarifies the nature of the content and redaction. Every word earns its place.
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?
Despite having no output schema, the description is adequate for a one-parameter fetch tool: it specifies the content type (full markdown text), the source of the slug, the verbatim nature, and the redaction caveat. Missing details like error handling on invalid slugs are minor and would not impede correct invocation.
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?
The schema already fully describes the single required parameter 'slug' with an example, so schema coverage is 100%. The description adds the meaningful constraint that the slug must come from research_journal, which is useful, but it does not add syntactic or format details 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: retrieving the full markdown text of one published research document by slug. It explicitly points to research_journal for the list, thereby distinguishing itself from sibling tools like research_journal (which lists) and other retrieval tools.
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 clearly implies the prerequisite workflow: first consult research_journal to obtain a valid slug, then call this tool with that slug. It does not enumerate exclusions or alternatives, but for a simple single-resource fetch this is sufficient context.
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 has a clear, distinct purpose: fleet_overview summarizes all sleeves, sleeve_record drills into one, gate_status tracks the go-live gate, kill_list logs rejected ideas, research_journal lists documents, research_note fetches a single document, and site_guide explains the platform. The only close pair is fleet_overview vs. sleeve_record, but their scopes (global vs. single sleeve) prevent confusion.
All tool names follow the same lowercase snake_case pattern with two tokens separated by an underscore (e.g., fleet_overview, gate_status, research_note). There are no mixed conventions like camelCase or inconsistent verb styles.
Seven tools is ideal for a read-only transparency platform. Each tool covers a distinct aspect of the domain without redundancy, and the count is well within the typical well-scoped 3–15 range.
The tool set fully covers its stated purpose: aggregate and per-sleeve performance, research journal and note retrieval, failure records, gate status, and self-description. There are no obvious dead ends—users can start at the overview, drill into details, and access all published documentation.
