ctxshot-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: context_stats estimates token cost, pack_context generates a project brief, and session_brief writes context to a file. No overlap or ambiguity.
Naming Consistency4/5All names use lowercase underscores and are descriptive. However, pack_context is verb-noun while context_stats and session_brief are noun-noun, showing minor inconsistency.
Tool Count4/5With only 3 tools, the server is tightly scoped for context management. The number is slightly low but covers the essential operations, making it appropriate.
Completeness4/5The tools cover the main use cases: estimating cost, generating a brief, and writing session context. Minor gaps like viewing or deleting context could exist, but the core workflow is complete.
Average 3.6/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 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 failing
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.
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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?
No annotations are provided, so the description bears full responsibility. It indicates a non-destructive read ('estimate token cost') but fails to disclose return format, side effects, or auth needs. The added context is minimal beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently convey purpose and usage guidance. Front-loaded: first sentence states the core action, second adds context. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 undocumented parameters and no output schema or annotations, the description is insufficient. It does not clarify parameter effects, return value, or tie to sibling tools beyond implied differentiation. More detail is needed for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with no parameter descriptions. The description offers no explanation of 'compact,' 'diff,' or 'root,' leaving agents to guess their meaning. It fails to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates token cost of a context pack, without returning full markdown. It distinguishes itself from siblings: pack_context likely returns full markdown, session_brief provides a session summary. The verb 'estimate' specifies the operation type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description suggests usefulness for before/after comparisons, indicating when to use. It implicitly differentiates from pack_context by noting it does not return full markdown. However, it lacks explicit exclusions or alternative suggestions beyond the sibling context.
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 carries full burden. It discloses that it writes to a file using git diff, but does not mention whether it overwrites, if a git repo is required, or any side effects. Lacks important safety details for a write operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no extraneous information. Front-loaded with the action and purpose, and ends with usage guidance. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and two optional parameters, the description covers the basic purpose and usage context. However, it omits details like whether the file is overwritten, the format of the packed context, and dependencies (e.g., git). Marginally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. Description does not add much beyond the schema's parameter descriptions, but does hint at defaults (e.g., output file relative to root). Not enough to raise the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it packs compact context with git diff and writes to .ai/context.md. Differentiates from sibling tools by specifying a specific output file and use of git diff, though does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to call: starting a new AI coding session or switching tasks. Does not provide when-not-to-use or alternative tools, but the given 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?
With no annotations provided, the description carries full burden. It discloses the output size range (200-2000 tokens) and contents, implying a read-only operation. Missing details include potential side effects (none expected), auth needs, and whether it caches or reads files beyond what's listed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core output and purpose. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the main use case and output. With 5 optional parameters and no output schema, it provides enough context for an agent. Minor gaps exist (e.g., no mention of whether it modifies any state), but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 does not add additional meaning beyond the schema; parameters are already well-documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a lightweight markdown project brief with specified contents (tree, npm scripts, README/AGENTS excerpt, optional git diff). It distinguishes from general repo reading or Repomix but does not explicitly differentiate from sibling tools context_stats and session_brief.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using the tool 'at session start instead of reading the whole repo or running Repomix,' providing clear context for when to use it. It does not, however, state when not to use it or compare directly to sibling tools.
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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- Evaluate tool definition quality.
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