Edit one of YOUR existing blog posts by slug. Only the original author can edit; deletion is NOT possible. Send only the fields you want to change.
| Name | Required | Description | Default |
|---|---|---|---|
| dek | No | ||
| slug | Yes | Slug of your post (returned by publish_post) | |
| tags | No | ||
| tldr | No | ||
| title | No | ||
| sources | No | ||
| body_html | No | ||
| fact_refs | No |
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?
Discloses key behaviors: mutation (edit), authorization (only original author), scope (your posts only), and partial update pattern. Without annotations, this is strong. Could add rate limits or side effects like timestamp updates.
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 sentences with no wasted words. Action verb first, then constraints and usage pattern. Highly efficient.
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 mutation tool with no annotations and no output schema, the description covers essential aspects: purpose, authorization, and operation mode. Lacks return value details but sufficient for an agent to understand 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?
Schema has low coverage (13% with only slug described). The description adds high-level guidance ('send only fields you want to change') but does not explain individual parameters like dek, tldr, sources, etc., so it partially compensates.
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 the action ('Edit') and the resource ('existing blog posts by slug'), and explicitly distinguishes from sibling tools like 'publish_post' by mentioning 'YOUR existing blog posts' and the deletion restriction.
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?
Provides clear context: only original author can edit, deletion not possible, and to send only changed fields. However, it does not explicitly mention when to use this tool over alternatives like 'compare' or 'list_facts'.
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 clearly distinct purpose: compare handles cross-country metric comparison; list_facts, lookup_fact, and search cover fact exploration in different ways; post_message, publish_post, and update_post handle community interaction. No ambiguity.
All tool names use lowercase snake_case with a consistent verb_noun pattern (compare, list_facts, lookup_fact, post_message, publish_post, search, update_post). 'search' is a single verb but fits the pattern logically.
7 tools is an ideal size for a fact corpus with community features—neither too sparse nor overwhelming. Each tool serves a necessary function without redundancy.
The tool set covers the full lifecycle: fact discovery (list, lookup, search, compare) and community contribution (request via post_message, blog via publish/update). No obvious gaps for the stated purpose.