destroy_tasksSoft-deletes a task; it is excluded from subsequent lists but the row is retained for history. Descendants are not auto-promoted.
| Name | Required | Description | Default |
|---|---|---|---|
| kwargs | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint, idempotentHint), the description adds crucial context: the soft-delete nature, exclusion from lists, row retention, and that descendants are not auto-promoted. This fully informs the agent of side effects.
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 tight sentences, front-loaded with the core action, and no redundant or unnecessary words. Every phrase adds value.
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 one-parameter delete tool with strong annotations, the description is largely complete. It explains side effects and hierarchy behavior, though it omits return format and permission requirements, which are less critical given the output schema absence.
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 description coverage is 0%, and the description does not explain the single 'pk' parameter or the 'kwargs' wrapper. The schema only provides 'The id of the task,' so the description adds no value for parameter understanding.
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 a specific verb (soft-deletes) and resource (task), and clearly distinguishes from a hard delete by noting row retention. It also differentiates from sibling destroy_* tools by targeting tasks specifically.
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 when to use this tool (when you want to remove a task from lists but keep history) but does not explicitly state alternatives or exclusions. There is no mention of when not to use it, such as for permanent deletion.
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.
Most tools are clearly scoped to a specific resource and action, but a few near-overlapping pairs (e.g., list_attachments vs list_taskattachments, create_tasktags vs add_tag_tasks) could cause misselection without close reading. Descriptions are detailed enough to resolve most ambiguity.
The dominant verb_noun CRUD pattern (create_, list_, retrieve_, update_, partial_update_, destroy_) is consistent and predictable. However, non-standard pluralizations (companys, resumeentrys, taskdependencys) and a handful of irregular names (task_assign_user, move_relate_to_tasks) introduce minor inconsistencies.
With 83 tools, this server is far beyond a well-scoped MCP surface, even for a feature-complete project management suite. The sheer volume will overwhelm agents and make selection inefficient, clearly falling into the extreme-mismatch range.
The toolset provides thorough lifecycle coverage across companies, projects, tasks, sprints, attachments, comments, dependencies, tags, reminders, resume entries, tickets, and users. Missing operations like company deletion or task-attachment creation appear intentional and are worked around via existing tools.