list_blog_postsList published articles from the Median blog, newest first. Optionally filter by category or a search term matched against the title.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many posts to return (default 20, max 50). | |
| search | No | Match against the post title. | |
| category | No | Filter to one category slug or name. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description does not contradict them. It adds minimal behavioral context beyond the annotations, only mentioning ordering ('newest first') and optional filters, which mostly restate parameter definitions. No side effects, auth needs, or rate limits are disclosed.
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 concise, using two sentences to convey the essential purpose and optional parameters without redundancy or fluff. It is well-structured and easy to understand.
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 read-only list operation with no output schema required, the description is complete. It covers the core functionality (listing, ordering, filtering) and does not need to explain return types or pagination, as these are not specified in the schema. The simplicity of the tool makes this sufficient.
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 provides descriptions for all three parameters, achieving 100% coverage. The tool description adds meaningful context by specifying that results are ordered newest first and explicitly stating that filters are optional, which supplements the schema. This slightly exceeds the baseline for high schema coverage.
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 tool's function: listing published articles from the Median blog, newest first, with optional filters. It distinguishes itself from sibling tools by specifying the resource (blog posts) and the brand (Median), making it distinct from other list_* 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 implies usage for retrieving multiple blog posts with filtering and ordering, but does not explicitly state when not to use it or mention alternatives like get_blog_post. However, the context of sibling tools (e.g., get_blog_post) makes the distinction implicit, and the description is self-explanatory.
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.
Tools mostly demand exactly one job: the list/explain/score path is clearly labeled per domain, and the START-HERE markers guide entry points. The fuzzy spots are get_conf_lefts and get_evidence_recipe (both refinement steps after list_compliance_obligations) plus list_services vs get_company_overview (they overlap on what Median does); these are distinguishable from the descritions but are the kinds of pairs that could send an agent the wrong way.
All twelve names follow the same verb_noun snake_case convention with consistent verbs: list the collections (_lists), get facts/computed refinements, explain single-item detail, and score the assessment. The pair structure (list vs explain vs proof) makes the intent predictable from the name for the first decode.
Twelve tools is right within the ideal for a domain-focused server: seven true domain tools (compliance + books) and five content/take-usational helpers. The content cluster (services, overview, pricing, blog, blog_post) is a bit tangential to a compliance/books mission, but this is a company-fronting server, so the zone works with a reason.
Both workflows close their loop: compliance has list → explain → confounders → evidence, and books has list → explain → score, with no obvious dead-end in either. Minor residuals exist (no explicit tool for showing covered versus non-covered states, other collaboration across the two domains), but an agent can work out these as of today's.