crewlog

by quantbagel

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct purpose: Linear issue operations, Slack queries, activity log actions, and coordination tools. No two tools overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun snake_case pattern (e.g., get_issue, search_slack, log_work). Minor abbreviation in 'whats_next' is acceptable.
Tool Count5/5
12 tools is well within the ideal range and covers all necessary actions for team coordination without being excessive.
Completeness4/5
The tool set covers core workflows: issue lifecycle, Slack context, activity logging, and status queries. Minor omissions like issue deletion or Slack messaging are acceptable given the domain scope.
Average 4/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. However, it only states 'search by text' without disclosing any behavioral traits like result scope, sorting, or limitations. Missing critical context for safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no unnecessary words. Front-loaded with purpose. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity (2 params, no output schema), the description should at least specify return format, pagination, or scope. It omits these, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to explain parameters. It only mentions 'by text' for query and says nothing about limit, its behavior, or formatting. Fails to add meaning beyond the schema.
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 clearly states the action (search Linear issues by text) and specifies when to use it (when you don't have an identifier), distinguishing it from siblings like get_issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when looking for issues by topic, feature, or bug without an identifier. Implies not to use when you have an identifier, but doesn't explicitly list when-not or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It confirms the tool adds a comment and supports markdown, but does not mention side effects (e.g., notifications), permissions, or idempotency. The behavior is minimally clear but leaves gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the core function; the second provides usage context. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 required params, no output schema), so the description is adequate but not thorough. Missing details like whether comments are appended, notification behavior, or character limits. Completeness is acceptable but could be better.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no new meaning beyond repeating 'markdown supported' and 'issue identifier like REF-123', which are already in the schema.
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 clearly states the action ('Add a markdown comment') and the resource ('Linear issue'). It distinguishes from siblings like update_issue and get_issue by specifying that it records comments rather than modifying issue fields or reading data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use the tool ('record findings, decisions, or progress'), but does not explicitly state when not to use it or mention alternatives like update_issue for editing issue description. Usage context is implied but exclusions are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must fully disclose behavioral traits. It only states 'Create' (mutation) without detailing side effects, permissions, or error handling. Basic purpose is clear, but critical behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The first sentence states the core purpose, and the second provides usage guidance. Highly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose and usage but does not explain return values (no output schema) or handle missing annotations. With 5 parameters and no output schema, some context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80% (4 of 5 parameters have descriptions). The tool description adds no additional parameter semantics beyond the schema, so a baseline of 3 is appropriate.
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 clearly states 'Create a new Linear issue' with specific usage scenarios (bug, follow-up, capture request), differentiating it from siblings like get_issue, update_issue, and search_linear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to call this tool ('when work is discovered that isn't tracked yet') with concrete examples, though it does not explicitly list when not to use it. The sibling tools provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully convey behavioral traits. Only states 'oldest first' and 'recent messages'. Lacks details on read-only nature, whether threads are included, rate limits, or required permissions. Important for an agent to know if the operation is safe and what it returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with key action and use cases. No fluff or redundant information. Examples are helpful and immediately convey context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with 2 parameters and no output schema. Description covers main purpose but omits output format, pagination behavior, and whether metadata (e.g., timestamps) is included. Could be more complete for a tool used to 'catch up' by detailing what the result looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 'channel' with a description, but 'limit' lacks explanation. Description adds no parameter details beyond schema. With 50% schema coverage, baseline is 3; description does not compensate by explaining parameter behavior (e.g., what 'limit' controls).
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?
Clearly states the tool fetches recent messages from one Slack channel, sorted oldest first. Provides concrete use cases (catching up on #eng, #standup, checking latest discussion). Distinguishes from 'search_slack' sibling by focusing on history retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly suggests when to call: to catch up or check latest discussion. Does not explicitly exclude cases (e.g., searching for specific terms), but context clearly differentiates from search siblings. Could mention alternative tools like 'search_slack' for search scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description implies read-only behavior (search) but does not explicitly confirm or mention any side effects, permissions, or data scope beyond the activity log.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences. First sentence states the core purpose; second adds valuable usage context. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema or parameter descriptions, the only missing context is parameter semantics and what results look like. The description provides good usage guidance but leaves key details unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no explanation of the 'query' or 'limit' parameters. The agent gains no additional insight beyond the raw schema properties.
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 clearly states 'Full-text search over the company activity log' and notes it includes teammate agent work summaries, distinguishing it from sibling search tools like search_linear and search_slack.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit scenarios: 'find who touched a topic, past decisions, or work that never made it into an issue.' Implies when to use but does not explicitly state when not to use or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It states the tool updates three fields and that state is matched by name, but does not disclose side effects (e.g., notifications, permissions required), whether updates are partial or full replacement, or what happens to unspecified fields. This is minimal for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with purpose, followed by usage guidance. Every sentence adds value with no repetition or filler. Structure is clear and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters (1 required) and no output schema, the description covers the main purpose and usage scenarios. It explains state matching behavior and typical use cases. It is mostly complete, though it could briefly note that the update is immediate or mention any required permissions for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter has a description. The tool description adds only one extra detail: 'State is matched by name against the issue's team workflow,' which provides context beyond the schema's 'Workflow state name, e.g. In Progress'. For other parameters, the description does not add significant meaning beyond what the schema already provides.
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 clearly states the tool updates a Linear issue's state, assignee, and/or priority, using specific verbs like 'starts work' and 'finishes'. It distinguishes from sibling tools like get_issue (read-only), create_issue (creation), and comment_on_issue (comments).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete usage scenarios: when a user starts work (state to 'In Progress'), finishes (state to 'Done/In Review'), or reassigns/reprioritizes. It explains state matching by workflow name. However, it does not mention when NOT to use the tool or explicitly list alternatives beyond the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It implies a read operation by stating 'who on the team is working on what right now,' but does not detail data freshness, permissions, scoping behavior without a team_key, or any side effects. The description is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two clear sentences: the first defines the purpose and the second gives usage guidance. No unnecessary words or repetition, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one optional parameter, no output schema, and no annotations, the description provides adequate context for what it does and when to use it. However, it does not explain the return format or the behavior when no team_key is provided, which could leave an agent uncertain about the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single parameter 'team_key' with a schema description. The main description adds no additional meaning about the parameter beyond what the schema already provides, so it meets the baseline for high schema coverage.
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 clearly states the tool returns current work assignments from Linear ('Who on the team is working on what right now, from Linear'). It distinguishes itself from sibling tools like get_issue (which retrieves a single issue) and search_linear (which is a general search) by focusing on real-time team status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to call the tool ('when the user asks what the team is doing, whether someone is already on a task, or before picking up work that might overlap with a teammate'). However, it does not explicitly mention when not to use it or name alternatives, though the context of sibling tools helps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explains what data is returned but does not state read-only nature or absence of side effects. The verb 'get' implies idempotency, but explicit statement would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states action and output details, second gives usage guidance. No unnecessary words; well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple one-parameter tool with no output schema. Description lists return fields and usage context. Missing details like pagination or error handling, but adequate for a straightforward retrieval.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter (identifier) with schema description 'Issue identifier like REF-123'. The description repeats the example, adding minimal value beyond schema. Baseline 3 as schema coverage is 100%.
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 states it retrieves full detail for one Linear issue by identifier, listing specific fields (description, state, assignee, priority, comments). This clearly distinguishes it from siblings like search_linear (searching) and update_issue (modifying).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises when to call: before starting work on an issue or when the user references an issue ID. Does not mention when not to use or compare to siblings, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses the company-wide scope and the multi-source merging behavior. Mentions the row count behavior with combined filters. However, it does not explicitly state that the tool is read-only, nor does it address pagination, ordering, or rate limits. Since no annotations are provided, the description carries full burden, and these omissions leave some behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences deliver the core purpose, usage guidance, and a behavioral nuance. Every sentence is informative and front-loaded with the tool's function. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the tool's purpose and usage well but lacks details about the output format. Since there is no output schema, the agent might need to infer the structure of timeline entries. For a feed tool, mentioning that each entry includes timestamp, actor, and source would increase completeness. However, the description is sufficient for basic invocation.
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?
The description adds meaning beyond the schema by explaining the source enum values concretely (e.g., 'Slack messages' maps to slack) and clarifying the interaction between source and actor filters. Since schema description coverage is 50%, the description compensates by illustrating how parameters combine. It does not detail the 'since' or 'limit' parameters beyond what the schema provides, but the overall semantic contribution is significant.
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 clearly defines the tool as a company-wide activity feed merging Slack, Linear, call summaries, and agent work logs. It provides specific example queries ('what happened', 'what did I miss'), distinguishing it from sibling tools like search_slack or search_linear which focus on single sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call the tool: when users ask about overall activity or catching up. Provides a behavioral note about row counts when both source and actor are set. Does not explicitly mention when not to use it or alternative tools, but the guidance is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full burden. It mentions 'with your visibility' hinting at permission-based results and describes supported query syntax behavior. It does not disclose potential rate limits or pagination details, but the transparency about query capabilities is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the primary action, and each sentence adds meaningful information without redundancy. It is highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters (one required), no output schema, and no annotations, the description provides adequate context for usage. It covers the query syntax and purpose but lacks information about the return format or behavior for empty results. However, it is reasonably complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must add meaning. It explains the 'query' parameter through examples of Slack syntax (e.g., 'in:#channel', 'from:@name'), adding value beyond the schema. However, it does not explain the 'limit' parameter or its constraints, leaving part of the parameter semantics unaddressed.
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 clearly states it searches Slack messages with a specific verb 'Search', identifies the resource 'Slack messages', and provides context about using Slack query syntax. It distinguishes itself by mentioning 'with your visibility' and gives use cases like finding past discussion, decisions, or context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Call this to find past discussion, decisions, or context about a topic,' providing clear usage context. However, it does not differentiate from the sibling tool 'slack_channel_history' or specify when not to use this tool, but the guidance is still strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently lists the four components of the response (briefing, in-progress issues, queue, urgent work), making the tool's behavior predictable. No side effects or contradictions are present.
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 a single paragraph of three sentences, efficiently conveying all necessary information. It is front-loaded with the action verb and context. Could be slightly improved with structured formatting, but remains concise and clear.
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 absence of parameters and output schema, the description is remarkably complete. It explains the tool's aggregation of multiple data sources (briefing, issues, queue, urgent work) and its expected use case, leaving no critical gaps for the agent to infer.
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?
The tool has no parameters, so baseline 4 applies. The description correctly implies that no input is needed, as the output is automatically scoped to the current user. No additional parameter documentation is required.
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 clearly specifies the tool's purpose: showing what the current user should work on next, including a daily briefing, in-progress issues, prioritized queue, and urgent unassigned work. It distinguishes from siblings like get_issue (single issue) and team_status (team view).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to call the tool: when the user asks what to do, what's next, about priorities, or at the start of a work session. It does not explicitly mention when not to use it, but the positive conditions are clear and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Clearly states it appends to a shared log. Does not mention permission requirements or reversibility, but for a simple write operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences total, with purpose front-loaded. Every sentence adds value: purpose, usage triggers, content length guideline. No wasted words.
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, no output schema, and full schema description coverage, the description is complete. It explains the tool's role, when to call, and how to format input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds valuable context beyond schema: 'ref' explained as issue id, repo area, or project; 'text' as what was done. This helps agents format correct inputs.
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 uses specific verbs ('append', 'summarize') and identifies the resource ('shared company activity log'). It distinguishes from sibling tools like 'activity_log' (likely read-only) and 'comment_on_issue' (issue-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call the tool: after completing significant work, making a decision, or starting a task. Also provides content constraints ('1-3 sentences'). Does not explicitly mention when not to use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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