The capture-coverage record: what the desk's observatory actually monitored and when, including gaps. Read this before treating any silence in the corpus as meaningful — the desk's own rule.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 behavioral burden. It usefully discloses that the record includes gaps and that silence should not be interpreted without consulting it. However, it does not explicitly state read-only semantics, return format, or other operational behavior, though the get_ name implies a safe retrieval operation.
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 short, information-dense sentences with no filler. The first defines the record's content, and the second provides the critical usage rule. The most important guidance is front-loaded.
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?
For a zero-parameter read-only tool with no output schema, this description is complete. It states what the record contains, that it includes gaps, and when to use it. Nothing essential is missing for an agent to call this tool correctly.
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 tool has zero parameters, so the schema already fully covers this dimension. The description adds useful context about what the record represents, but no parameter-level semantics are needed. Baseline 4 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 names a specific resource — the capture-coverage record — and defines its content as 'what the desk's observatory actually monitored and when, including gaps.' This is clearly distinct from the sibling tools like get_audit or get_boxscore. It lacks an explicit action verb like 'retrieves' or 'lists,' but the get_ prefix and 'Read this' make the purpose unambiguous.
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 gives a concrete when-to-use instruction: read this before treating any silence in the corpus as meaningful. This is an explicit, actionable usage rule. It does not name alternatives or state when not to use the tool, but the conditional guidance is strong enough for an agent to route correctly.
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 maps to a distinct resource or action: list versus get for corpus discovery, chain versus claim ledger versus storyboards for chain analysis, framing index versus boxscore for statistics, and submit/report/propose for reader input. Even adjacent pairs like get_audit and verify_piece are clearly separated by their different purposes.
All tools follow a consistent verb_noun snake_case pattern, with get_* for detailed retrieval, list_* for summaries, and action verbs for reader-facing inputs. The verb choice reliably signals the operation type throughout.
At 15 tools, the set sits at the upper end of the ideal range, but every tool addresses a distinct facet of the desk's public surface: discovery, deep detail, provenance, coverage monitoring, and reader interaction. No tool feels redundant or decorative.
The surface covers discovery, retrieval, chain analysis, provenance verification, corrections, and reader interaction, forming a coherent workflow with no dead ends. Minor gaps exist: boxscore days are only enumerated off-server, and letters are exposed only as excerpts rather than individually retrievable records.