livekit-agent-simulator

by quangdang46

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes (scaffolding, scenario management, execution, analysis). However, 'run_scenario' is an alias for 'execute_scenario', creating redundancy and potential confusion. Otherwise, boundaries are clear.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., 'list_scenarios', 'validate_scenario', 'compare_runs'). No mixing of conventions.
Tool Count5/5
12 tools is well-scoped for a simulation framework: covering project initialization, scenario management, execution, validation, and results analysis. Each tool serves a clear purpose.
Completeness4/5
The tool surface covers the core workflow (init, validate, execute, analyze). Minor gaps: no direct tool for creating/editing scenarios (only export) and no deletion management. The redundant alias is a slight detraction.
Average 3.1/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 361 commits in the last 12 weeks
- Last stable release on August 16, 2026
- 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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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. It only mentions that the tool reads a file and supports a prefix filter. It does not state that the tool is read-only, what side effects (if any) occur, or any auth requirements. The behavior of other parameters (e.g., limit, turn) is unaddressed.
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 short (two sentences) and front-loads the core purpose. However, it could be more efficient by also covering key parameters without adding length. It does not waste words but is overly sparse.
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 (7 parameters, 2 required, no schema coverage) and the existence of sibling tools, the description is insufficient. An output schema exists, so return values need not be explained, but the description fails to provide enough context for an agent to choose and configure the tool correctly without extensive schema exploration.
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 0%. The description adds meaning for only one parameter ('kind' describes prefix matching). The remaining six parameters (project_root, run_id, turn, limit, source, since_mono_ms) are not explained. The description does not compensate for the lack of schema descriptions.
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 action ('Read events.jsonl') and describes a specific filter capability (prefix match on 'kind'). This gives a clear sense of the tool's function, but it does not differentiate from sibling tools like get_run_report or list_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 usage guidelines are provided. There is no indication of when to use this tool over siblings (e.g., compare_runs, get_run_status). The description does not mention prerequisites, exclusions, or alternative tools.
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 provided, the description must fully disclose behavior. It mentions what the report contains but omits any side effects, prerequisites (e.g., run must be completed), or permissions. The minimal description leaves many behavioral aspects unspecified.
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 a single sentence with no wasted words. It quickly conveys the core output facets. Could be improved with structured formatting (e.g., bullet points) but is efficient.
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?
An output schema exists, so return value details are covered elsewhere. The description explains what is in the report, filling that gap. However, it misses operational context: when to call this vs siblings, prerequisites, and whether the run must be completed.
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 the description must add meaning for the two parameters. It does not. There is no explanation of what project_root or run_id represent, leaving the agent to infer from parameter names alone.
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 lists key components of the report (summary, judge verdict, suspicious turns, paths), making the output clear. However, it lacks an explicit verb stating the action (e.g., 'retrieves' or 'generates'), relying on the tool name. Distinguishes from siblings like get_run_log (log vs full report) but could be more explicit about scope.
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 such as get_run_log, get_run_status, or compare_runs. The agent receives no decision-making support for tool selection.
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 disclosure. It mentions the file path pattern and returned fields but omits important details such as error handling (e.g., what if the path doesn't exist), permissions required, or whether results are paginated. The behavior is partially transparent but lacks depth.
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 a single sentence, concise but missing key information about the parameter. It is front-loaded with the action and resource but fails to explain the parameter meaning. Slightly too terse given the need for parameter context.
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?
An output schema exists (true) but is not shown; the description lists three fields (id, tags, validity) which is helpful. However, without parameter explanation or usage comparisons to siblings, the description feels incomplete. For a simple list operation, it is adequate but not comprehensive.
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 schema has one required parameter (project_root) with no description (0% coverage). The description does not explain what project_root is, its expected format, or how it relates to the file path. The agent must infer that project_root is a directory containing `.agent-sim/scenarios/`. This is insufficient.
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 verb ('List'), the resource ('all scenarios'), and specifics about location (`.agent-sim/scenarios/*.jsonl`) and included fields (id, tags, validity). This distinguishes it from sibling tools like execute_scenario or validate_scenario.
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 like list_runs or validate_scenario. The description assumes the agent knows to use it for listing scenarios but does not exclude cases where filtering or validation might be needed.
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 full burden but only lists validation checks. It does not disclose whether the tool is read-only, what happens on failure (e.g., errors), or any side effects. The presence of an output schema mitigates slightly, but behavioral context is minimal.
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 a single, front-loaded sentence with no wasted words. However, it is excessively terse and omits necessary details, balancing conciseness against completeness.
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 has 2 parameters and an output schema, the description should provide enough context for correct invocation. It specifies what is validated but omits the validation result format, prerequisites, and any constraints, leaving gaps.
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 the description must add meaning beyond the schema. The description mentions 'scenario file' but does not explain the two parameters (scenario_id, project_root) or their roles, leaving them underdefined.
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 validates a scenario file with specific aspects: schema, required Persona brief, and PassCriteria lint. This distinguishes it from sibling tools like execute_scenario or list_scenarios, which perform different actions.
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 alternatives. While it can be inferred that validation should precede execution, the description lacks any when-to-use, when-not-to-use, or alternative recommendations.
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 does not disclose behavioral traits such as read-only nature, permissions needed, side effects, or state changes. It only states the export action but lacks deeper behavioral context.
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 a single sentence of 15 words, concise and front-loaded with the key action. It earns its place with no wasted words, though could add structure.
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 low complexity with 2 parameters and an output schema (assumed as JSON). However, the description fails to provide parameter details or usage context, which are needed for completeness. The description is too brief to fully inform an AI agent.
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%. The tool description provides no information about the parameters (scenario_id, project_root) beyond what is in the schema. The description does not add meaning or context for the parameters.
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 (export), the resource (parsed scenario), the output format (JSON), and lists the components (Persona, Execute run params, Dispatch flag, PassCriteria). It distinguishes this tool from siblings like execute_scenario or validate_scenario.
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. No explicit use cases, prerequisites, or exclusions. Only implied from sibling tool names.
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 indicates it is a read-only operation (listing history) and notes ordering (newest first). It does not disclose potential effects, rate limits, or whether it modifies data, but the read behavior is implied.
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 a single, concise sentence that front-loads the core purpose. No unnecessary words, but it could be slightly more structured for clarity.
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 does not explain the required project_root parameter or the limit parameter. It omits important usage context, making it incomplete for a tool with multiple parameters.
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 only adds context for scenario_id (optional filter) but omits explanation of the required project_root parameter and the limit parameter (default 20). With 0% schema description coverage, this leaves gaps for the agent.
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 lists run history from SQLite, ordered newest first, with optional filtering by scenario_id. However, it does not explicitly distinguish it from sibling tools like get_run_log or compare_runs, which may also relate to 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 such as compare_runs or get_run_log. The description only mentions optional filtering but lacks context on typical use cases 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 bears full burden. It only says 'Run a simulation' without disclosing side effects, permissions, or behavioral traits. This is minimal transparency for a run/mutation tool.
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 sentence with zero redundancy. It is front-loaded and efficient, conveying its key point immediately.
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 has 2 required parameters, no schema descriptions, and no annotations, the description is too sparse. It lacks context about the simulation's nature, prerequisites, or output, leaving significant gaps for correct invocation.
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 coverage is 0% with no parameter descriptions. The description does not explain the meaning or format of 'scenario_id' or 'project_root', adding no value beyond the structural schema definition.
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 states 'Run a simulation,' clearly indicating the action and resource. It distinguishes from the sibling 'execute_scenario' by noting that the latter is preferred for validate-then-run, providing differentiation.
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 preference hint ('prefer execute_scenario for validate-then-run'), which implies when to use the alternative. However, it does not explicitly state when to use this tool or exclude other cases, leaving usage context somewhat implicit.
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 bears full responsibility. It lists comparison metrics but does not disclose side effects, authorization needs, rate limits, or whether it's read-only. The behavioral profile is minimal.
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 a single concise sentence that front-loads the action and lists key comparison points. However, it lacks any structural organization like sections or bullet points, which could improve scanability.
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 complexity (3 required parameters, 0% schema coverage, no annotations), the description fails to compensate. It does not explain how the diff is presented (despite an output schema existing), and parameter meaning is absent, 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?
The input schema has 0% description coverage, and the tool description does not explain any parameter (e.g., what 'project_root' is or that 'run_id_a' and 'run_id_b' must be valid). The parameter semantics are completely absent.
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 ('diff') and the specific aspects compared (duration, turns, tool errors, etc.), and the tool name 'compare_runs' is distinct from siblings like 'list_runs' or 'get_run_report'.
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 use for comparing two runs but does not explicitly state when to use or when to avoid, nor does it mention alternatives such as 'get_run_report' for single-run analysis. Usage is inferred rather than guided.
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 available, the description correctly implies a read-only operation by stating it retrieves status. It lists the returned fields, though it does not explicitly mention that the tool has no side effects. Overall, it is sufficiently transparent for an agent.
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-structured sentence that delivers essential information without superfluous words. It is front-loaded with the main purpose and outputs.
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 the tool's simplicity (2 parameters, no nested objects, output schema exists), the description covers the output but omits parameter details. It is adequate for a basic understanding but lacks completeness regarding input semantics.
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 0%, so the description must compensate. However, it does not explain the parameters (run_id, project_root). While the parameter names are somewhat self-explanatory, an agent may need more context about formats or values. This is a significant gap.
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 retrieves the status of a run from SQLite, listing possible statuses (running/done/failed) and additional data (turn count, duration). It is specific and distinguishes from sibling tools like get_run_log or get_run_report.
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 such as get_run_log or compare_runs. The description does not provide context for prerequisites or scenarios where another tool would be more appropriate.
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?
Discloses main actions (scaffold directory, gitignore) but lacks detail on edge cases: what if .agent-sim exists? Does it overwrite or error? How does it modify .gitignore? No annotations provided to compensate.
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?
Single sentence with all key points (verb, resource, location, gitignore). No filler, but could briefly mention prerequisite or idempotency without significant bloat.
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?
Covers core purpose and action for a simple tool with one parameter and output schema. Missing details on error handling, idempotency, or prerequisite that project_root is a git repository.
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 has 0% parameter description coverage, so description adds value by indicating 'project_root' is the target repo path. However, no specifics about expected format (absolute/relative) or validation.
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 verb 'Scaffold' and resource '.agent-sim/' with specific files 'config.yaml + smoke scenario', and action 'gitignore it'. Clearly distinguishes from sibling tools which deal with scenarios and runs.
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?
Implied usage as initialization step before other tools, but no explicit guidance on when to use, prerequisites (e.g., git repo), or when not to use (e.g., if already scaffolded).
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 discloses the two-step process (validate then execute) and the return type (validation + run result), but does not mention side effects, state changes, or logging. With no annotations, the description carries the full burden and provides only basic 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?
The description is a single sentence that is front-loaded with the tool's purpose and immediate result. Every word is necessary; no wasted content.
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?
The tool has 2 parameters, no annotations, but an output schema (not shown). The description covers the core functionality and return type, but lacks details on prerequisites (e.g., project initialization), error cases, or how to interpret the validation result. Given the sibling set, more context on sequencing with other tools would be helpful.
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 0%, so the description must add meaning. It specifies that scenario_id comes from .agent-sim/scenarios/*.jsonl files and project_root identifies the project, which adds value beyond the schema. However, it does not explain formats, constraints, or how to find valid scenario IDs.
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 validates then executes a scenario from a specific directory (.agent-sim/scenarios/*.jsonl) and returns both validation and run result. This distinguishes it from siblings like validate_scenario (validation only) and run_scenario (likely execution without validation).
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 the tool performs validation before execution but does not explicitly state when to use this tool versus siblings like execute_scenarios (batch) or run_scenario. No guidance on prerequisites or alternatives.
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 carry the full burden of disclosing behavioral traits. It only states what the tool does but does not mention side effects, destructive potential, authentication needs, or other behavioral aspects. For a tool that likely mutates state, this is a significant gap.
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, efficiently front-loaded with purpose and key usage details. No superfluous words; every sentence adds necessary information.
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 the complexity of running multiple scenarios with optional filtering, the description covers the main choices but lacks specifics on error handling, behavior when no files are valid, or non-functional aspects. The presence of an output schema reduces the need to explain return values, but comparison with similar tools is minimal.
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 0%, so the description must compensate. It explains two of three parameters: scenario_ids (omit to run all) and tag (optional filter). However, the required 'project_root' is not described, relying on its self-explanatory name. This adds some value but is incomplete.
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 'Execute multiple scenarios', which is a specific verb+resource. It distinguishes from the sibling 'execute_scenario' (singular) by the plural form, and further clarifies behavior by explaining that omitting scenario_ids runs all valid files.
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 context: 'Omit scenario_ids to run all valid files; optional tag filter (e.g. smoke).' This gives guidance on when to omit parameters. However, it does not explicitly compare with alternatives like 'run_scenario' or 'execute_scenario', though the plural name implies usage for multiple scenarios.
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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