list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
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?
Annotations already declare readOnly, idempotent, and non-destructive. The description adds value by specifying that it returns active subscriptions by default, the specific output fields, and that 'include_inactive' can change behavior. This goes beyond the structured annotations without contradicting them.
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, zero filler. The first sentence states the action and return fields; the second provides usage context. Every word earns its place, making it highly scannable and 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?
The tool is simple with one optional parameter and no output schema. The description covers return fields, default behavior, and usage scenarios. It lacks mention of pagination or limits, but for a list tool this is not a significant gap given the context. 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?
Schema coverage is 100%, and the parameter 'include_inactive' is fully described in the schema. The description's mention of 'active subscriptions' aligns with the default false, but it does not add new semantic detail beyond the schema. Baseline 3 applies because the schema handles the parameter documentation.
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 uses a specific verb ('List') and resource ('caller's active subscriptions'), and clearly distinguishes from siblings by focusing on reading vs. creating/canceling (subscribe/unsubscribe). It also lists exact return fields, leaving no ambiguity about what the tool does.
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 states when to use: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This gives concrete scenarios and implies alternatives (subscribe/unsubscribe). It provides clear practical guidance for an agent.
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 ORCID-specific tools (record, search, works, work) are reasonably distinct, but the set is dominated by unrelated Pipeworx/Polymarket tools, several of which overlap heavily (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions). ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx, creating genuine misselection risk.
Naming conventions are mixed with no consistent pattern: nouns like 'record', 'work', 'works', and 'education' sit alongside snake_case verb phrases like 'search_within', 'validate_claim', and 'generate_llms_txt', plus proprietary 'ask_pipeworx' / 'pipeworx_feedback' names. While readable, the styles are inconsistent enough that an agent cannot predict tool names from the domain.
37 tools is far too many for a server scoped as 'Orcid': only roughly 7 tools (record, works, work, education, employment, search, search_within) actually relate to ORCID. The remaining ~30 tools cover prediction markets, npm dependencies, AI visibility, and generic Pipeworx/Polymarket functionality, which is a severe scope mismatch.
For read-only ORCID access, the surface covers full records, works, education, employment, and registry search, with semantic search over fetched records as a useful addition. However, it lacks other common ORCID activity types (funding, peer review, distinctions), profile metadata beyond summaries, and any create/update/delete lifecycle operations, leaving notable gaps for a server claiming to serve ORCID data.