update_project_issueChange the status, severity or detail of a project issue, attach the task that fixes it, or record how it was resolved. Use this instead of logging a duplicate issue.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| title | No | ||
| detail | No | ||
| source | No | ||
| status | No | ||
| task_id | No | Task that fixes this issue. | |
| issue_id | Yes | ||
| severity | No | ||
| resolution | No | What was done, required in spirit when closing an issue. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is a mutating but non-destructive operation. The description adds that it can change status, severity, or details, attach a task, and record resolution, but it does not disclose possible side effects, reversibility, or any special behavior when closing an issue. There is no contradiction with the 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 two sentences with no filler. The first sentence lists the distinct update actions compactly, and the second provides routing guidance. Key information is front-loaded.
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 tool with 9 parameters, sparse schema descriptions, and no output schema, the description gives the core actions but omits several updateable fields and does not clarify edge cases such as whether resolution is expected when setting status to resolved. It is adequate for common usage but not fully 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 description coverage is only 22%, and the description compensates partially by naming status, severity, detail, task_id, and resolution. However, it leaves url, title, source, and issue_id unexplained, and for task_id/resolution it largely repeats what the schema already says. It adds meaning to several previously undocumented fields, but the coverage gap is still significant.
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, 'Change', and a clear resource, 'a project issue', then enumerates the concrete update actions: status, severity, detail, attaching a fixing task, and recording resolution. It also contrasts this with 'logging a duplicate issue', which helps distinguish it from the sibling log_project_issue tool.
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 phrase 'Use this instead of logging a duplicate issue' explicitly tells the agent when to prefer this tool over the closest alternative: when the issue is already known and should be updated rather than re-created. This provides clear when-not guidance and names the relevant alternative behavior.
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 target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.
The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.
At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.
The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.