Orchestrate Codex

by Meapri

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct aspect of recipe orchestration: context policy, continuing runs, explaining recipes, fallback chains, fetching run state, listing recipes, planning, and starting runs. No overlaps are apparent.
Naming Consistency4/5
All tools follow the 'orchestrate_' prefix with clear verb_noun or noun phrases, but some like 'orchestrate_fallback_chains' and 'orchestrate_context_policy' use noun-noun patterns while others use verb-noun. Still mostly consistent and predictable.
Tool Count5/5
With 8 tools, the set is well-scoped for a recipe orchestration server, covering planning, execution, state retrieval, and explanation without being overwhelming.
Completeness4/5
The surface covers core lifecycle operations (plan, start, continue, get run, explain, list) and supporting features (fallback chains, context policy). A minor gap is the absence of a cancellation or stop-run tool, but it's not critical for the stated purpose.
Average 3/5 across 8 of 8 tools scored. Lowest: 2.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 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.
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description only says 'show', implying a read operation but providing no details on side effects, permissions, or output behavior.
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?
Very concise (one phrase) but lacks structure and informative content; front-loaded but insufficient.
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 no output schema and no annotations, the description is too minimal to cover behavioral context, return format, or what constitutes a 'chain'.
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?
No parameters exist (schema coverage 100% empty), so the description adds no parameter info; baseline 4 applies as per guidelines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Show default capability→fallback leaf tool chains' uses cryptic notation and vague verb 'show', failing to clearly state what the tool does or distinguish it from siblings like orchestrate_get_run or orchestrate_list_recipes.
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 guidance on when to use this tool versus alternatives; sibling tools listed but no differentiation 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?
No annotations provided, so description carries full burden. It implies read-only behavior ('Explain'), but does not disclose whether there are any side effects, authentication needs, or rate limits. The description lacks behavioral details beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but not concise in a helpful way; it omits important details. It is under-specified rather than efficiently informative.
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 one parameter, no annotations, no output schema, and multiple sibling tools, the description is incomplete. It does not explain return values, prerequisites, or how to obtain a recipe_id.
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 0%, so description must compensate. It does not mention the required 'recipe_id' parameter at all, leaving the agent with no guidance on what value to provide.
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 verb 'Explain' and the resource 'recipe', listing specific aspects (stages, doc_class, context policy, default leaf bindings). However, it does not differentiate from sibling tools like orchestrate_context_policy or orchestrate_plan_recipe, making it less clear when to choose this one.
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 guidance on when to use this tool vs alternatives. There is no mention of prerequisites, context, or exclusions.
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 must disclose behavioral traits. It only mentions building a static plan, with no information on side effects, permissions, or output format. This is insufficient.
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 and front-loaded, with two sentences. However, it sacrifices completeness for brevity; many details are missing.
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?
Given 6 parameters (none described), no output schema, and no annotations, the description is severely under-informative for an agent to use the tool effectively.
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 0%, and the description adds no meaning to any of the 6 parameters (model, prompt, system, bindings, recipe_id, instruction). Without parameter descriptions, the agent cannot use them correctly.
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 builds a 'static plan (steps + suggested tools)' and distinguishes it from start_run for stateful execution. However, 'static plan' could be more specific.
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 advises to 'prefer start_run for stateful execution', giving some guidance on when not to use this tool. But it lacks explicit when-to-use scenarios or exclusion criteria beyond that.
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?
The description reveals that the tool auto-executes gather stages, returns next_action, and does not call other servers. However, with no annotations, it omits details on error handling, idempotency, authentication, or the effect of optional parameters.
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 concise with two sentences, front-loading the main action and adding key behavioral notes. It could benefit from more structured format, but remains 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 8 parameters, low schema coverage, no annotations, and no output schema, the description lacks completeness. It fails to explain the return format fully, the meaning of 'local gather stages', or how bindings and other parameters interact.
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 25%, yet the description adds no parameter-level details. It does not explain how parameters like model, prompt, or bindings affect the run, nor does it clarify the role of recipe_id beyond being required.
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 starts a supervised run and auto-executes local gather stages. It differentiates by noting it does not call other MCP servers, but does not explicitly distinguish from sibling tools like orchestrate_plan_recipe or orchestrate_continue_recipe.
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 no guidance on when to use this tool versus alternatives. It mentions what the tool does but not the context for its selection, such as prerequisites or conditions for use.
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 but only discloses the basic action and valid parameters. It does not describe side effects, permissions, rate limits, error handling, or output format – leaving significant behavioral gaps.
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 a single, well-formed sentence with no wasted words. It is appropriately concise for a simple tool with one parameter.
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 low complexity (one parameter, no nested objects), the description lacks important context: it does not explain what a context policy is, what the return value looks like (no output schema), or how the doc_class values affect the response. This leaves the agent with incomplete understanding.
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 lists the enum values (durable, change, transform, direct) but these are already present in the input schema. It adds no explanation of what each doc_class means or how they differ, failing to compensate for 0% schema description 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 action ('Return') and the resource ('context policy') with a specific qualifier ('for a doc_class'), and lists the allowed enum values, making the purpose unambiguous and distinct from sibling tools which focus on recipes or runs.
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 guidance is provided on when to use this tool versus alternatives (e.g., orchestrate_plan_recipe, orchestrate_get_run). The description only states what it does, leaving the agent to infer usage context without explicit when-to-use or when-not-to-use instructions.
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, and the description offers no behavioral details beyond the core function. It does not state whether the operation is read-only, idempotent, or if any side effects occur.
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 a single succinct sentence front-loaded with the verb and resource. Every word is meaningful with no fluff.
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 description lacks any mention of return format, pagination, or scope. Given no output schema, the description should provide more completeness about what the listing includes.
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 zero parameters and 100% schema description coverage, so the description does not need to add parameter meaning. Baseline is 4 for zero-parameter tools.
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 (list) and the resource (built-in supervised orchestration recipes). It distinguishes from sibling tools like orchestrate_continue_recipe or orchestrate_plan_recipe by focusing on listing rather than executing or explaining.
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 implies usage when one needs to list recipes, but provides no guidance on when not to use it or how it differs from alternatives. No explicit context for selection among siblings.
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 bears full responsibility for behavioral disclosure. It reveals the fallback behavior on leaf failure and that state/run_id are passed, but it does not disclose side effects (e.g., persistent mutations), required permissions, or response characteristics. The transparency 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 two sentences with no fluff. The first sentence captures the primary purpose and key inputs, and the second adds critical failure behavior. Information is front-loaded and efficiently presented.
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 7 parameters, nested objects, no output schema, and no annotations, the description is incomplete. It omits details about return values, full state structure, and parameters like stage_id, auto_local, and result_text, which are essential for correct invocation.
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 schema has 0% description coverage, so the description must compensate. It explains only 3 of 7 parameters (run_id, state, success) by mentioning them in context. Missing explanations for error, stage_id, auto_local, and result_text leave significant gaps for the agent.
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 advances a run after a leaf tool result, specifying the core action (advance) and resource (run). It distinguishes from siblings like 'orchestrate_start_run' (starting) and 'orchestrate_get_run' (querying) by focusing on post-leaf continuation.
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 when to use: after a leaf tool result. It also provides guidance on failure handling by instructing to set success=false to trigger fallback_tools with a specific chain. However, it does not mention when not to use or compare with alternative siblings like 'orchestrate_fallback_chains'.
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 carries full weight. It discloses the 'same process only' constraint but does not mention side effects, authentication, or error behavior. For a simple read operation, this is minimally 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?
A single sentence that is front-loaded with the core purpose ('Fetch run state') and includes a critical constraint. No redundant words.
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 tool with one parameter and no output schema, the description is adequate but lacks details on what 'run state' contains and what 'same process only' means in practice. More context on return values would improve completeness.
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 schema description coverage is 0%, and the description only notes that run_id is used to fetch state. It provides no format, example, or additional semantics to compensate for the bare schema. A higher score would require more detail on the parameter's meaning.
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 ('Fetch'), the resource ('run state'), and the identifying parameter ('run_id'), and adds a specific constraint ('same process only'). This distinguishes it from sibling tools like orchestrate_start_run or orchestrate_plan_recipe.
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 limits usage to runs within the same process, which guides when to use. However, it does not name alternative tools for cross-process or other scenarios, though the constraint 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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