deepseek-as-subagent
Server Quality Checklist
Latest release: v0.0.1
- Disambiguation5/5
The two tools serve completely distinct purposes: one for delegating tasks to DeepSeek and one for health checking. There is no ambiguity or overlap.
Naming Consistency4/5Both tools use snake_case, but 'delegate_to_deepseek' is descriptive while 'ping' is a single-word convention. The pattern is mostly consistent, with a minor deviation.
Tool Count3/5With only 2 tools, the server is minimal but appropriate for its focused role as a sub-agent delegator. The health check is essential, but more tools (e.g., cancellation) could be added.
Completeness4/5The server covers its core purpose: delegating tasks and verifying availability. No obvious missing operations for its narrow scope, though a status polling tool could be useful.
Average 4.7/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 4 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.
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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes that DeepSeek runs its own agent loop with specific tools, saves main-conversation tokens, and returns a summary including files, turns, tokens, and issues. It also advises verifying results. Could mention potential failures or permissions but overall transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections and bullet points for good/bad fits, front-loading the main purpose. Every sentence adds value, though the list of tools (Read/Write/Edit/Bash/etc.) could be slightly trimmed but is still informative.
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 complexity of the tool and that an output schema exists (though not shown), the description covers parameters, use cases, and return value. Sibling is only 'ping', so no confusion. Could mention edge cases or error handling, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, the description provides detailed semantics for both parameters: 'task' is a clear description with success criteria and file paths; 'context' is optional additional context for project-specific knowledge. This significantly adds value beyond the schema property names.
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 that the tool delegates a task to DeepSeek as a sub-agent, listing its capabilities (Read/Write/Edit/Bash/etc.) and specifying the scope of tasks (batch/repetitive/mechanical). It distinguishes itself from the only sibling tool 'ping' which is a simple health check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Excellent usage guidelines: explicitly lists 'Good fits' (e.g., extract i18n keys, translate, scan logs, bulk refactors) and 'Bad fits' (architectural design, bug analysis, tasks needing project-specific idioms), advising the agent to 'do it yourself instead' for bad fits.
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 exist, so the description fully bears the burden. It states the return values (version, mode, config loadable) and implies a safe read operation. However, it does not explicitly state that the tool is non-destructive or requires no permissions, but for a health check, this is acceptable.
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 three sentences long, front-loaded with 'Health check.', and contains no unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and the presence of an output schema (which likely details return structure), the description still lists what the tool returns and provides usage context relative to the sibling tool. It is fully adequate for an agent to understand and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so baseline 4 applies. The description does not need to add parameter information.
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 is a health check that confirms server aliveness, and distinguishes it from the sibling tool 'delegate_to_deepseek' by explicitly mentioning its use before that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use this before delegate_to_deepseek if you're not sure whether DeepSeek is configured.' This tells the agent exactly when to use this tool and even mentions an alternative.
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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