capture-and-slack-mcp

by baho0

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clear, distinct purpose: capture without posting, capture and post, send existing files, ask questions, check status, and two blocking wait variants. No two tools overlap in functionality.
Naming Consistency5/5
All tool names use snake_case with a consistent verb_noun pattern (ask_review, capture_window, check_review, send_to_slack, wait_for_reply, wait_for_review). The slightly longer 'capture_window_and_post' still follows the same structure and is clear.
Tool Count5/5
With 7 tools, the server is well-scoped for its purpose: capturing screenshots and managing Slack review workflows. Each tool adds necessary functionality without bloat or redundancy.
Completeness4/5
The tool set covers the main workflow: capture, post, review, follow-up. A minor gap is the lack of a tool to post a regular Slack message without a review, but the core review-focused flow is well-supported.
Average 4.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 11 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that no Slack call is made, so no token or scope is needed, and that the screenshot is returned for inspection. However, it does not describe the output format or any side effects, which is a gap given no annotations are provided.
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, front-loaded with the core purpose, and each sentence provides unique value (purpose then usage pattern). No wasted words.
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 core functionality and usage pattern well, but it does not mention the return value format. Given the schema fully documents parameters, the description is mostly complete for a tool with no output schema.
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 schema already documents all parameters. The description adds no additional meaning about parameters like 'trim', 'window', or 'allow_fullscreen', thus no added value beyond the schema baseline.
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 captures a screenshot without posting, and distinguishes from the sibling 'capture_window_and_post' by noting it does not call Slack and does not require tokens/scopes.
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 suggests composing with 'send_to_slack' to inspect and optionally post the image, indicating when to use this tool versus alternatives. However, it does not explicitly list exclusion criteria or enumerate sibling alternatives.
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 discloses blocking behavior, return values, and timeout, but it does not state whether the tool has side effects (e.g., modifying state) or the polling mechanism, though param descriptions cover polling interval.
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, front-loaded with the core action, and every sentence adds value—defining behavior and providing usage guidance.
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 no output schema, the description explains blocking, conditions, return values, and timeout behavior. It lacks explicit mention of polling frequency but covers it in the `poll_seconds` parameter description.
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%; the tool description reinforces the use of `since_ts` and `timeout_seconds` but adds little new information beyond the schema's parameter descriptions.
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 blocks until a thread reply is posted after `since_ts` or timeout, and contrasts with sibling tools like ask_review and wait_for_review by specifying usage after ask_review timeout.
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 advises using this tool after ask_review timed out, providing clear context for when to use it, but does not explicitly state when not to use it or compare with all siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description thoroughly covers behavior: it posts to the review thread, pings the channel so away reviewers notice, blocks waiting for an answer, returns 'answered' with the answer or 'still_awaiting' with an ask_id on timeout, and includes polling and timeout mechanics. No contradictions.
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 with no fluff. The first sentence front-loads the core action, and the second adds necessary details about behavior and return values. Every sentence earns its place.
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 covers the primary use case, return values (answer vs. still_awaiting), and the follow-up action (wait_for_reply). However, it omits error handling (e.g., invalid review_id) and does not detail the channel parameter's effect on pinging. Overall sufficient but not exhaustive.
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% description coverage, so the baseline is 3. The description adds some context (e.g., explaining poll_seconds and timeout_seconds usage) but does not significantly enhance the already clear schema descriptions.
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 asks a follow-up question in Slack and waits for an answer. It distinguishes itself from siblings like wait_for_reply and send_to_slack by specifying the exact mechanism (posting in thread, pinging channel) and noting that it blocks for a reply.
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 instructs to 'ALWAYS use this instead of asking in the console,' providing a clear when-to-use. It also mentions wait_for_reply as a follow-up step. However, it does not compare against other sibling tools like capture_window or check_review, leaving some ambiguity.
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 are provided, so the description carries full burden. It details key behaviors: fallback to fullscreen (with allow_fullscreen parameter explaining error vs silent posting), default window title via environment variable, and that thread_ts is for replying. Minor omission is the exact return value, but echo_image parameter partially addresses output.
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 main description is two concise sentences. Parameter descriptions are detailed but not verbose. Overall well-structured and easy to parse, though slightly longer due to complete parameter documentation.
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 8 parameters, no output schema, and no annotations, the description covers the tool's purpose, use case, and parameter details well. However, it does not explicitly describe the return value when echo_image is false (e.g., whether it returns a review_id or just posts), leaving some ambiguity.
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 the description adds value beyond schema. For example, title parameter explains its dual role as card header and file title, window parameter explains default env var and special values like 'active', and allow_fullscreen explains error behavior. This extra context justifies above baseline 3.
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 'Screenshot the running app window (X11/KDE) and post it to Slack as a review.' It provides a specific verb, resource, and action, and explicitly distinguishes from sibling tool send_to_slack by specifying when to use each.
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 explicitly states when to use this tool ('only when no offscreen render exists') and when to prefer the alternative ('otherwise prefer send_to_slack with a repro-rendered PNG'). This is strong usage guidance.
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, but description discloses blocking behavior, timeout, return verdict format, and re-call hint. Does not cover auth or error cases, but key behavioral traits are addressed.
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 effective sentences with zero waste. Front-loaded with main action, return format, and pairing hint. Every sentence earns its place.
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 well-described schema and no output schema, description adequately covers return format and pairing. Could mention blocking duration limit implicitly, but overall complete for the use case.
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 100% (baseline 3). Description adds value: explains review_id origin, channel default (SLACK_DEFAULT_CHANNEL), and the re-call hint on timeout. Enhances parameter understanding.
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 explicitly states the verb 'Block' and the resource 'human reaction/reply in review thread', distinguishing from siblings like check_review (non-blocking) and wait_for_reply (replies only).
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?
Clear context: blocks until human reacts/replies or timeout, and explicitly pairs with send_to_slack's review_id. Lacks explicit when-not-to-use or alternatives but is sufficient.
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?
Declares non-blocking behavior and immediate return. Lists possible return values. With no annotations, it carries full burden; while it implies read-only ('read the current review verdict'), it does not explicitly state no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, key information front-loaded. Every sentence adds value.
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 no output schema, it lists possible statuses. Explains non-blocking behavior and usage pattern. Missing error handling details, but sufficient for a simple read 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 100% (baseline 3). Description adds context: review_id origin and channel default behavior, enhancing beyond 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?
Description clearly states it reads the current review verdict and lists possible statuses. Distinguishes from sibling wait_for_review by emphasizing non-blocking nature.
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?
Explicitly instructs to use in polling loop and provides alternative wait_for_review for blocking scenario. Covers both when and when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It thoroughly discloses behaviors: posts a root anchor message (Block Kit task card when title/status/checks/links given), threads images, returns JSON with review_id and permalink, explains notify behavior (broadcasts to channel when replying), and default channel. No 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?
The description is efficient, with three sentences that front-load the main action and detail. Parentheticals add necessary context without being overly verbose. It avoids unnecessary words, though could be slightly more compact.
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 10 parameters, 1 required, and no output schema, the description is very complete. It explains the overall flow, return value structure (review_id and permalink), parameter usage for all key fields, and mentions polling with wait_for_review. It covers essential behavioral details for safe and effective use.
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 description coverage is 100%, so baseline is 3. The description adds meaningful context beyond the schema: e.g., title is 'used as the Block Kit card header AND the file title in Slack,' checks are 'Name→value facts shown as card fields,' images are 'Posted in order as ONE Slack message,' and notify is 'Ignored for a new review.' These details enhance understanding.
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 'Post one or more existing image files to Slack as a review.' It specifies the action (posting), resource (image files to Slack), and purpose (review). It also distinguishes from siblings by calling itself 'the primary tool' and noting the returned review_id can be polled with wait_for_review, setting it apart from other tools like ask_review or capture_window.
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 clear usage context: 'This is the primary tool: pair it with a repro/test that renders the result to a PNG.' It explains that it posts a root anchor message and threads images, and that the review_id can be polled. However, it does not explicitly state when not to use this tool or compare it directly to siblings, so it lacks exclusion guidance.
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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