Skip to main content
Glama

Update a bug

update_bug

Update a bug's fields or status; set status to in_progress when starting a fix and resolved when it ships, and replace the solution with the actual fix applied.

Instructions

Partial update of a bug. Most common use: status transition. Follow the lifecycle one step at a time: open (wild) → in_progress (chasing) → resolved (catched). Set status="in_progress" the moment you start the fix, not after it lands — it is the only marker that someone is already on this bug, so a parallel agent can see the work in flight instead of duplicating it. Then set "resolved" once it ships. Skipping straight from open to resolved returns a warning (not a rejection) — acceptable when the fix was genuinely instant. Other patchable fields: title, description, solution, score (0–8 change-risk), metadata. When resolving, rewrite solution to what you actually applied — at report time it held the plan, and leaving a stale plan there is worse than leaving it empty. To mark a bug as fixed, prefer status="resolved" over delete — that preserves the history of what eroded the tree. When resolving, you may record the shipped release in metadata.resolvedVersion (e.g. "v2.3.1"); metadata is replaced wholesale, so include existing keys you want to keep.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesBug id.
slugYes
patchYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does so thoroughly. It discloses the warning on skipped states, the wholesale replacement of metadata, the need to rewrite solution to the actually-applied fix, and the parallel-agent visibility implications of in_progress.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average, but every sentence contributes workflow guidance or behavioral caveats. It is front-loaded with the core purpose and then expands into actionable rules; slightly more brevity would improve it, but it is not padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (nested patch object, multiple patchable fields, state transitions) and no output schema, the description covers all critical behavioral aspects: transition ordering, warnings, metadata replacement, solution rewriting, and the resolved-vs-delete tradeoff. It is contextually complete for an AI agent selecting and invoking the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33%, so the description must compensate. It adds significant meaning for status (lifecycle one step at a time), solution (rewrite before resolving), metadata (wholesale replacement, include existing keys), and score (0–8 change risk). The slug parameter remains undocumented, which holds this back from a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Partial update of a bug' and immediately identifies the most common use: status transition. It clearly distinguishes update_bug from sibling tools like create_bug and delete_bug by specifying what parts can be patched and how status changes drive the lifecycle.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance: set in_progress when starting a fix, set resolved when shipped, and prefer resolved over delete to preserve history. It also explains the parallel-agent signaling rationale and notes that skipping straight to resolved is acceptable with a warning, providing clear usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bepuljang/umtri-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server