Skip to main content
Glama

log_issue

Log a bug or unexpected behavior immediately to preserve the issue across interruptions and session boundaries, returning a trackable issue ID.

Instructions

Open a new issue. Returns the issue ID.

MANDATORY: call this IMMEDIATELY when you encounter a bug, regression,
or unexpected behavior — BEFORE writing fix code. Logging up-front
means the issue survives interruptions and session boundaries.

Side effects: appends an `issue` event to .projectmem/events.jsonl,
creates an issue file in .projectmem/issues/, updates summary.md,
and marks this issue as the active one for subsequent
record_attempt calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryYesOne-line description of the bug or unexpected behavior (~140 chars recommended). Becomes the issue title and is matched by search_events.
locationNoOptional file path or component where the issue manifests (e.g., 'src/auth.py' or 'login/double-submit'). Used by precheck_file to surface this history later.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, so description bears full burden. It enumerates side effects: appends to events.jsonl, creates issue file, updates summary.md, marks active issue. This fully discloses behavioral impacts without contradictions.

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?

Description is relatively concise with five sentences covering purpose, usage, and side effects. Front-loaded with core function. Could potentially be tightened, but no extraneous information.

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 low complexity (2 params, no nested objects, output schema exists), description adequately covers all aspects: purpose, usage, side effects, parameter details, and return value. No gaps identified.

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 100%, but description adds value beyond schema: suggests ~140 chars for summary, states it becomes issue title and is searchable, and clarifies location is used by precheck_file. While helpful, it does not radically augment schema meaning.

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?

Description explicitly states 'Open a new issue' and specifies the return value (issue ID). Verb 'log_issue' combined with description clearly indicates the action on a resource. Differentiates from sibling tools like 'get_issue', 'record_attempt', 'record_fix' by focusing on issue creation.

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?

Provides explicit directive: 'MANDATORY: call this IMMEDIATELY when you encounter a bug, regression, or unexpected behavior — BEFORE writing fix code.' This gives clear when-to-use context and emphasizes immediacy, leaving no ambiguity about the tool's purpose relative to other actions.

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/riponcm/projectmem'

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