codex-dobby-mcp

by Averyy

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.4
Disambiguation5/5
Each tool has a uniquely defined purpose with no overlap. brainstorming, building, planning, researching, reviewing, validating, and reverse-engineering are clearly distinct activities, and run-management tools are separate.
Naming Consistency4/5
Most tools use a single verb (brainstorm, build, plan, etc.) while run-management tools use verb_noun pattern (start_run, get_run). This is mostly consistent with minor deviation.
Tool Count5/5
11 tools is well-scoped for a code development assistant. Each tool serves a distinct phase or function without unnecessary duplication.
Completeness5/5
The tools cover the full lifecycle from idea evaluation (brainstorm), planning, implementation (build), review, validation, reverse engineering, and run management. No obvious gaps for the stated purpose.
Average 3.4/5 across 11 of 11 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues 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 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.
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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.
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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 present, so the full burden is on the description. It does not disclose whether the tool is read-only, what side effects exist, or what kind of output to expect. The only behavioral hint is the recommended timeout.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, but the phrase 'broader roots' is unclear and wastes space. The timeout recommendation is useful but could be integrated more elegantly. The description is not front-loaded with the most critical information.
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 the tool's complexity (9 parameters, required prompt and repo_root) and lack of output schema details, the description is insufficient. It does not explain what the tool returns or how to interpret results, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 11% (only repo_root is described). The tool description does not explain any of the 9 parameters, leaving their purposes largely undefined. The agent would have no way to understand parameters like 'extra_roots' or 'important_context' without additional context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool investigates binaries using reverse-engineering tooling. It is specific about the resource (binaries) and the action (investigate). However, the phrase 'broader roots' is vague and does not add clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a recommended timeout but gives no guidance on when to use this tool vs sibling tools (e.g., research, review). No context about prerequisites or typical scenarios is provided.
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?
Without annotations, the description carries the full burden. It hints at potentially destructive behavior ('implement a change') but does not detail safety, reversibility, permissions, or verification scope.
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 essential purpose. Every sentence adds value with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 9 parameters (many optional), an existing output schema, and no annotation support, the description is far too sparse to guide correct invocation. It omits critical context about parameters, return values, and side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 11%, and the tool description adds no parameter meaning. The sole schema description for 'repo_root' is helpful, but the description itself ignores all 9 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool implements a change, runs verification, and reports results. It provides a specific verb-resource combination but does not differentiate from sibling tools like 'review' or 'validate'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Only a recommended timeout is provided. No guidance on when to use this tool versus alternatives (e.g., brainstorm, plan, review). No context about prerequisites or exclusions.
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?
Without annotations, the description carries the full burden. It states 'read-only mode and report findings', implying no side effects, and recommends a timeout. However, it does not disclose timeouts, error handling, what constitutes a 'report', or how results are structured (output schema exists but not described).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences but lacks structure; it frontloads purpose but omits parameter guidance. Every sentence serves a function, yet more detail on parameter usage would improve utility without adding excessive length.
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 8 parameters (many optional), low schema coverage, and no annotations, the description is incomplete. It does not explain how parameters interact or when to use optional fields, leaving significant gaps for correct invocation. Output schema exists but is not described.
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 only 13% (low); only 'repo_root' has a schema description. The description does not explain the meaning or usage of the other 7 parameters (e.g., 'files', 'model', 'reasoning_effort'), failing to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose ('Investigate code, docs, and context in read-only mode and report findings') with a specific verb and resource. It distinguishes from siblings like 'build' or 'review' but does not explicitly differentiate from similar analysis tools like 'brainstorm' or 'reverse_engineer'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a recommended timeout ('20 minutes (1200s)') but offers no guidance on when to use this tool versus alternatives, no when-not-to-use conditions, and no mention of prerequisites or selection criteria among siblings.
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, the description carries full burden for behavioral traits. It only mentions a recommended timeout, lacking information on side effects, authorization needs, rate limits, or internal operations (e.g., external API calls). Minimal transparency.
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 very concise (two sentences) and front-loaded with the primary purpose. However, it could include essential parameter hints without becoming verbose, so it slightly underperforms on completeness for the conciseness trade-off.
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?
Despite having 8 parameters and an output schema, the description does not explain what the outputs look like or how to use optional parameters. Leaves significant gaps for an agent to infer proper usage, especially given the lack of schema descriptions.
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 low (13%), so the description must compensate. However, it adds no parameter-level details beyond the recommended timeout. Parameters like 'files', 'model', 'reasoning_effort' remain unexplained, leaving the agent without guidance on usage.
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 the tool evaluates an idea, scopes an MVP, and recommends whether to build. The verb 'evaluate' and resources 'idea' and 'MVP' provide specific purpose. Implicitly distinguishes from sibling tools like 'plan' and 'research' by focusing on evaluation and recommendation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. Does not mention prerequisites, suitable idea types, or when to avoid. Only provides a recommended timeout, which is a parameter hint, not usage 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 are provided, so the description carries full responsibility for behavioral disclosure. It states 'List' implying a read-only operation, but does not discuss what 'recent' means, whether results are ordered, if it shows incomplete runs, or any potential side effects. It lacks details on pagination, rate limits, or authentication needs.
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, with the first sentence stating the core purpose and the second providing a practical use case. It is front-loaded, no redundant or filler content, and every sentence adds value.
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?
For a simple listing tool with an output schema (present but not visible), the description is adequate but not complete. It does not clarify ordering, time frame for 'recent', or behavior of 'limit'. These gaps could lead to incorrect assumptions by the agent.
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?
The description does not mention parameters at all. The input schema covers repo_root with a description and limit with a default, but 50% of parameters lack schema descriptions. The main text adds no additional meaning beyond what the schema provides, failing to explain how 'limit' works or constraints like the path requirement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List recent Dobby runs for a repo,' which conveys a specific action on a specific resource. It also adds context about recovering task ids after timeout, which helps understand its utility. However, it does not explicitly differentiate from sibling tools like 'get_run' or 'wait_run', though the plural 'runs' implies listing multiple.
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 gives a concrete use case: 'recovering task ids and results after a caller-side timeout.' This is helpful for when to use. However, it does not mention exclusion criteria, such as not using this tool to get a single run (use 'get_run' instead) or to monitor ongoing runs (use 'wait_run'). No guidance on 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?
No annotations are provided. The description states 'without editing files', indicating it is non-destructive. However, it does not disclose other behavioral aspects such as side effects (e.g., if it saves state), required permissions, or behavior on timeout. With zero annotation coverage, the description carries the full burden but only partially addresses it.
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 primary purpose. Every sentence adds value: purpose and a timeout recommendation. No unnecessary information.
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?
The tool has 8 parameters and no annotations. The description omits explanations of key parameters (e.g., prompt, files, model) and does not clarify the plan's output format despite an output schema. It is insufficient for an agent to correctly invoke the tool without additional knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 8 parameters with only 13% coverage (repo_root described in schema). The tool description adds no parameter documentation whatsoever, leaving the agent to guess the meaning of prompt, files, model, etc. Given low schema coverage, the description must compensate but fails to do so.
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 'Break down a task and propose a scoped plan without editing files', which clearly identifies the action (break down, propose), the resource (a scoped plan), and distinguishes from siblings like build (edits files) or brainstorm (generates ideas).
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 provides a recommended timeout, which helps in usage, but does not specify when to use this tool versus alternatives like brainstorm or build. No explicit when-to-use or when-not-to-use guidance besides the implication from 'without editing files'.
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 are provided, so the description carries full responsibility for behavioral disclosure. It mentions the default single-agent behavior and fan-out capability, but does not disclose whether the tool is read-only, destructive, requires authentication, or what side effects (e.g., file modifications) occur. Key behavioral traits are 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?
The description is two sentences with zero wasted words. It front-loads the core purpose and then provides practical timeout guidance. Every sentence adds value, making it 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 the tool's complexity (9 parameters, output schema present), the description is incomplete. It does not explain what the tool returns, how it uses parameters like 'files' or 'extra_roots,' or the meaning of 'important_context.' The output schema exists but is not referenced, leaving the agent without guidance on expected results.
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 only 22%, but the description does not compensate. It only implicitly guides the 'timeout_seconds' parameter via a recommendation, and fails to explain important parameters like 'prompt', 'files', 'model', 'reasoning_effort', or 'important_context.' The description adds minimal semantic value 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 tool's purpose: 'Review code with one agent (default) or fan out to multiple specialist agents.' This is a specific verb+resource combination that distinguishes it from sibling tools like 'brainstorm' or 'build.' The mention of multiple specialist agents adds clarity about capability.
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 gives context on when to use single vs. multi-agent review and provides recommended timeouts, but it does not explicitly state when not to use the tool or how it compares to siblings like 'validate' or 'research.' No explicit exclusion or alternative references are given.
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 must disclose behavior. It states the tool runs validation commands and reports results, and mentions timeout. However, it does not clarify whether commands modify files, fail behavior, or permission needs, leaving gaps in 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, front-loaded with the primary action and a key recommendation. Every sentence contributes value with no wasted words.
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?
Despite having an output schema, the description is minimal for a tool with 8 parameters, no annotations, and low schema coverage. It does not explain the role of most parameters or the output structure, leaving an agent under-informed.
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 only 13% (one param documented). The description adds meaning only for timeout, leaving 7 parameters (files, model, extra_roots, etc.) unexplained. The tool description fails to compensate for the low 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's action ('Run existing repo validation commands') and the resource ('repo'), with specific verbs (build, test, lint) and result reporting. It distinguishes from siblings like 'build' (which likely only builds) and 'review'.
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 a recommended timeout (10 minutes), offering practical usage guidance. It does not explicitly contrast with sibling tools, but the name and context make the purpose clear. No when-not or alternative directives are given.
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 partially reveals behavior (read operation, file-based recovery) but lacks details on idempotency, error handling, or auth requirements. 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?
Two sentences, each adding value: first states core function, second adds important context. No redundancy or 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?
For a simple retrieval tool with an output schema (not shown), the description gives sufficient context. Missing a note on task_id origin or error cases, but overall complete enough.
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 coverage is 50% and the description adds no information about the parameters themselves. The need for repo_root is only explained in the schema, not the description. No additional semantics 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 tool gets the status or final ToolResponse for a Dobby run using a task ID, distinguishing it from siblings like start_run or wait_run. It is specific and not a tautology.
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 a specific use case (recovering results after a timed out call), but does not explicitly exclude other contexts or compare to alternatives like wait_run otherwise.
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, the description fully bears the transparency burden. It clearly states the tool returns immediately with a task id and runs in the background. It doesn't disclose cancellation, error handling, or resource limits, but the core async behavior is well communicated.
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 very concise: two sentences plus a recommendation, all front-loaded with the core action. Every sentence adds value with no redundancy or fluff.
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 complexity (11 parameters, many optional) and presence of an output schema, the description explains the output (task id) and how to use it with siblings. It doesn't detail the output schema structure, but the core flow is covered. It adequately addresses the tool's role among 11 siblings.
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 low (18%), so the description should compensate. It mentions tool, prompt, repo_root as parameters implicitly but does not elaborate on all 11 parameters. The description adds context for usage but doesn't map to individual parameters beyond the overall flow.
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 action: 'Start a Dobby tool in the background and return immediately with a task id.' It clearly distinguishes from sibling tools like wait_run, get_run, and list_runs by explaining the asynchronous behavior and follow-up patterns.
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 when-to-use guidance (short timeouts), follow-up patterns (wait_run with single or multiple task_ids), and alternatives (get_run/list_runs for non-blocking peek). This gives the agent clear decision criteria.
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?
No annotations are provided, so the description carries full burden. It explains blocking behavior, return on completion vs. timeout, cancellation shielding ('Background tasks are shielded from waiter cancellation'), timeout clamping, and details of return format (ToolResponse for completion, RUNNING lookup for timeout).
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 a single paragraph but well-organized: front-loaded main purpose, then parameter usage, then timeout details. Every sentence adds value, though slightly verbose with client-specific timeout examples. Could be split into bullet points for readability.
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 complexity (blocking vs. timeout, multiple modes, cancellation, clamping) and presence of an output schema, the description covers essential behaviors: return values for both completion and timeout, shielding from cancellation, timeout bounds. It doesn't discuss error cases like invalid task_id, but that's acceptable for a wait tool.
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 description coverage is only 25% (repo_root has description). The description adds meaning to all parameters: task_id (wait for one run), task_ids (wait for first of several), repo_root (always pass active root), timeout_seconds (default and clamp details). This compensates well for the low 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?
Description clearly states the tool blocks until a background run finishes, with specific usage modes for one run (task_id), multiple runs (task_ids for whichever finishes first), or all live runs. The verb 'wait' matches the name, and it's distinct from siblings like get_run (non-blocking) and start_run (launches work).
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?
Description explicitly says 'Call after start_run' and details parameter variations. It gives timeout guidance with client-specific defaults (Claude Code, Codex CLI, etc.). While it doesn't explicitly say 'don't use this for non-blocking checks', the context makes it clear that this is for blocking; alternatives like get_run are implied but not named.
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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Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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