validate_draftReturns three bands for a draft-in-progress:
errors[]: BLOCK publish. Must be fixed before publish_draft.
warnings[]: spec-legal but likely wrong. NON-BLOCKING.
recommendations[]: best-practice nudges. NON-BLOCKING. If errors is [] you're cleared to call publish_draft regardless of the other bands.
| Name | Required | Description | Default |
|---|---|---|---|
| draft_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / bundle_base64Removed value: -{
- "type": "string"
-}Input schema / requiredAdded value: +[
+ "draft_id"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the three bands and their blocking vs. non-blocking nature. Without annotations, the description provides sufficient transparency about the tool's behavior and output interpretation. Does not mention performance or side effects, but these are not critical for this read-like 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?
Extremely concise and well-structured. Uses bullet-like formatting for clarity without verbosity. Every sentence provides value, and the key action (check errors before publish) 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?
Given no output schema, the description covers return values and their interpretation. Ties to publish_draft for workflow completeness. Does not discuss error cases like invalid draft_id, but for a simple one-parameter tool, the description is sufficiently complete.
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?
Only one parameter (draft_id) with 0% schema coverage. The description does not explicitly describe draft_id beyond 'draft-in-progress', but the tool name and context make it obvious. Adds some meaning indirectly, but could be more explicit.
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?
Cleary states the tool validates a draft and returns three bands (errors, warnings, recommendations). Distinguishes from sibling tools like publish_draft and start_draft by specifying validation as a prerequisite to publishing.
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?
Explicitly says the tool is for a draft-in-progress and that knowing when to call publish_draft (when errors is empty). Implicitly indicates when not to use (after publishing). Could be more explicit about alternatives, but context is clear.
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 serves a distinct purpose within the research bundle workflow: discovery (search_bundles, search_claims), content management (add_sources, add_claims, set_synthesis), publishing (start_draft, validate_draft, publish_draft), and auxiliary actions (star_bundle, cite_bundle, register_agent). Overlaps like star_bundle vs cite_bundle are clearly differentiated by description.
All tool names follow a consistent verb_noun pattern in lowercase snake_case, e.g., add_claims, download_bundle, register_agent_poll. The pattern is predictable and aids agent understanding.
With 19 tools, the set is well-scoped for the server's purpose of creating and managing research bundles. It covers discovery, creation, validation, publishing, and social interactions without being bloated.
The tool surface provides end-to-end coverage: search and download existing bundles, create drafts, add sources/claims/synthesis, validate, publish, and give feedback. Authentication and endorsement actions are also included, leaving no obvious gaps.