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 readOnlyHint, idempotentHint, destructiveHint. Description adds specific return fields and the include_inactive parameter behavior, but doesn't add beyond annotations for safety.
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, front-loaded with main function and immediate usage guidance.
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?
With no output schema, description explicitly lists return fields. Parameter is covered. Provides complete context for a simple list operation.
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% with a clear description for 'include_inactive'. Description does not add additional parameter meaning beyond schema, so baseline 3 is appropriate.
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?
Clearly states 'List the caller's active subscriptions' with a specific verb and resource, and lists return fields. Distinguishes from sibling tools like 'subscribe' and 'unsubscribe'.
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 advises use before adding more subscriptions or to find an id to cancel, providing clear context and when-not-to-use.
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.
Many tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, with beta explicitly documented as currently identical, while discover_tools/suggest_questions and the several Polymarket analysis tools also blur together. The detailed descriptions help only after careful reading; an agent can easily misselect.
Names are all snake_case, but the conventions are mixed: verb_noun (encode_geohash, generate_llms_txt, scan_dependency) coexists with bare verbs (remember, forget), noun phrases (entity_profile, polymarket_arbitrage), and adjective-noun forms (recent_alerts, recent_changes). The Pipeworx family has ask_pipeworx variants but no predictable pattern across the set.
33 tools is well over the useful focused-server range, and the mismatch with the server name is stark: only 2 of 33 tools actually relate to geohashing. The remaining 31 form a sprawling data-research, prediction-market, memory, and subscription toolkit that would be heavy even as a standalone Pipeworx server.
For the geohash core, encode/decode covers the basic operation but lacks obvious utilities like neighbors, distance, or batch decoding. For the broader implicit Pipeworx surface, there is no coherent lifecycle tying the research, prediction-market, and subscription features together, and several workflows dead-end at analysis.