w3c_specDetail for one web-standards spec by shortname ("WCAG21", "css-grid-1", "html") or title fragment ("web content accessibility"). Returns title, status, organization (W3C/WHATWG), working groups, series, official URL, editor's-draft URL. Example: w3c_spec({ spec: "WCAG21" }). Accepts shortname/name/title too.
| Name | Required | Description | Default |
|---|---|---|---|
| spec | No | Spec shortname or title fragment. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "spec": "WCAG21"
+ },
+ {
+ "spec": "css-grid-1"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds value by listing the specific return fields (title, status, organization, etc.) and input flexibility, which provides useful behavioral context beyond annotations.
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 three sentences long, covering purpose, return data, and input flexibility. It is concise without being overly terse, though structuring with bullet points could improve scanability. No unnecessary information.
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 the simple parameter (one optional string) and no output schema, the description adequately covers input formats, example usage, and return fields. The annotations compensate for missing output schema by declaring idempotency and read-only nature, making the description complete for this tool's complexity.
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 covers 100% of parameters with a description, but the tool's description enriches this by explicitly stating that it accepts shortname, name, or title, and provides concrete examples. This goes beyond the schema's brief description.
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 identifies the tool's purpose: retrieving details for a single web-standards spec using a shortname or title fragment. It specifies the verb 'returns' and the resource, and distinguishes from sibling w3c_search by focusing on single spec retrieval.
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 provides usage context by mentioning acceptable inputs (shortname, name, title) and gives an example call. However, it lacks explicit guidance on when to use this tool versus the sibling w3c_search tool, which is a minor gap.
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.
The three ask_pipeworx variants plus deep_research and validate_claim overlap heavily on the same routing capability — ask_pipeworx_beta is even explicitly identical to ask_pipeworx right now. The polymarket tools (arbitrage/edges/edge_tracker/fill_risk/kalshi_spread) form a second cluster with fuzzy boundaries, and ai_visibility_check vs scan_competitor_ai_presence overlap. However, most other tools (w3c_search, spec, remember/recall/forget, subscribe/unsubscribe) have clear distinct roles.
Names are generally descriptive snake_case with recognizable prefix families (ask_pipeworx_*, polymarket_*, w3c_*), but verb usage is inconsistent: passive labels like ai_visibility_check and entity_profile sit alongside imperatives like recall, forget, subscribe, and resolve_. There's no uniform verb_noun or noun_pattern convention across the set.
33 tools is over the heavy threshold, and the count is wildly mismatched to the server's claimed identity: the server is named 'W3c' yet only 2 of 33 tools (w3c_search, w3c_spec) relate to W3C. The remaining 31 form a sprawling Pipeworx data/prediction-market service that would justify its own server, making this aggregation incoherent.
For its actual purpose (broad data research + prediction markets), the surface is fairly complete: search, grounded answers, deep research, comparison, entity profiles, entity resolution, memory, subscriptions, and feedback cover the main workflows. But for the server's stated W3C purpose, only search and spec-detail exist with no broader standards tooling. The domain mismatch makes completeness hard to credit.