unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=true), the description adds critical context: ownership enforcement, deactivation (not deletion), and that historical events remain available via recent_alerts. This significantly enriches the behavioral profile.
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 concise sentences: action, ownership constraint, and side effect. Every sentence provides unique value, with no redundancy or filler.
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 single-parameter tool with no output schema, the description covers the core behavior and consequences effectively. It omits return value or error details, but given the simplicity and availabile annotations, this is a minor gap.
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 already provides 100% coverage for the id parameter, stating it is the subscription id returned by subscribe. The description reinforces that it must be your own subscription, but adds no new syntactic or format details beyond the schema.
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 states 'Cancel a subscription by id' with a specific verb and resource, and clarifies the deactivation vs deletion behavior, making it distinct from siblings like subscribe and list_subscriptions.
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?
It clearly implies usage for canceling subscriptions you own, with ownership enforcement stated. However, it doesn't explicitly name alternative tools for other actions, leaving the comparison to siblings implicit.
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.
Multiple tools are near-duplicates: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share nearly identical behavior, and validate_claim overlaps heavily with ask_pipeworx_grounded. ai_visibility_check vs scan_competitor_ai_presence also overlap. dataset/organization vs search_datasets/search_organizations could confuse agents.
Naming is inconsistent: snake_case (ask_pipeworx, deep_research, entity_profile), long descriptive names (scan_competitor_ai_presence, polymarket_edge_tracker), and terse single words (dataset, organization). No coherent naming convention across the set.
37 tools is heavy, and most are Pipeworx platform tools (Polymarket analysis, npm dependency scanning, llms.txt generation, memory ops) that are far out of scope for a 'Datagouv Fr' French open-data server. Only ~6 tools (search_datasets, search_organizations, reuses_search, resources, dataset, organization) relate to the server's stated domain.
The data.gouv.fr browsing surface is reasonably complete: search datasets, search organizations, list reuses, fetch resources, get dataset/organization by slug. However the server lacks common catalogue operations like downloading a resource from a URL, inspecting dataset metadata details, or community/follow features — plus the bulk of tools target entirely different domains, leaving the actual data.gouv.fr scope thin.