pretalx-mcp

by kevinnz

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct resource and action: events, speakers, submissions, schedule, and reviews are clearly separated. Search and list variants are differentiated by search intent versus full listing, and summary tools are distinct from detailed get tools.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with the pretalx_ prefix, using lowercase snake_case throughout. The naming convention is uniform, making the tool set predictable and easy to navigate.
Tool Count5/5
With 14 tools, the server is well-scoped for a conference management domain. Each tool covers a necessary operation without redundancy, fitting the typical 3-15 tool range comfortably.
Completeness5/5
The tool surface comprehensively covers the read-only needs of a Pretalx event management system: events, speakers, submissions, schedule, and reviews are all addressed. It includes listing, getting, searching, and summarizing operations, with no obvious gaps in core workflows.
Average 2.9/5 across 14 of 14 tools scored. Lowest: 2.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
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.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions case-insensitive filtering and a flattening operation, but does not explain what 'flatten' means, whether the tool is read-only, what the return structure is, or any side effects. This is insufficient for a tool with zero annotation support.
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 short sentence and is front-loaded, but it is under-specified. 'Flatten' and 'filters' are vague, and no detail is provided, making the brevity a drawback rather than an asset.
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?
With no annotations, 0% schema coverage, and six parameters, the description leaves critical behavior unexplained. It does not clarify how filters combine, what include_raw does, or what flattening produces. The presence of an output schema does not compensate for the missing parameter and behavior semantics.
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 only says 'optional case-insensitive filters' without mapping to any of the six parameters. It does not explain the meaning of day, room, event, track, speaker, or include_raw, nor how filters interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses 'Flatten schedule sessions' as a verb-resource pair, but 'flatten' is ambiguous and does not clearly state that this tool lists sessions from a schedule. It also does not distinguish itself from siblings like pretalx_get_schedule or pretalx_find_schedule_conflicts.
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 guidance is provided. The description does not say when to use this tool versus alternatives such as pretalx_get_schedule or other listing tools. The phrase 'optional case-insensitive filters' implies usage but gives no 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?
With no annotations, the description carries the full burden of behavioral disclosure. 'Fetch one event in detail' is too vague to indicate what 'detail' entails, whether authentication is needed, or what the response structure is. It adds minimal 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 with no wasted words. It is concise and front-loaded with the action, but it is under-specified, which prevents a higher score.
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?
Despite the presence of an output schema, the description lacks essential context: no parameter explanations, no usage guidance, no behavioral notes, and no differentiation from siblings. This is inadequate for an agent to invoke the tool correctly.
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 description adds no meaning to the 'event' or 'include_raw' parameters. An agent has no information about what values to provide, what the parameters represent, or how they affect the call.
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 uses the verb 'Fetch' with the resource 'one event', clearly distinguishing it from sibling tools like pretalx_list_events. The phrase 'in detail' is somewhat vague but still conveys a single-object retrieval intent.
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 pretalx_list_events or other retrieval tools. It does not state prerequisites, typical use cases, or situations 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.
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. It only mentions a compact form, which hints at output shape but doesn't disclose pagination behavior, authentication needs, or what 'visible' entails. This is minimal and leaves the agent guessing.
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?
While the description is short, it is under-specified rather than concise. A single vague sentence without useful structure or front-loaded key details does not earn its place compared to more informative descriptions.
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 is simple (2 optional params) and has an output schema, but the description is too sparse to be complete. It lacks any context about event visibility, parameter semantics, or relationship to other list tools, making it insufficient for an agent to select and invoke correctly.
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 two parameters (limit, include_raw) with no descriptions, and schema description coverage is 0%. The description adds no meaning about these parameters, so an agent has no idea how to use them or what effect they have.
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 'List visible events in a compact form' clearly identifies the action (list) and resource (events), with 'visible' indicating a filter. It distinguishes from siblings like pretalx_get_event (singular) and pretalx_list_submissions (different resource), though it could be more explicit about what 'visible' means.
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?
There is no guidance on when to use this tool versus alternatives. No prerequisites, exclusions, or sibling comparisons are mentioned. The description only states what it does, not when it is appropriate.
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 available, and the description only adds 'compact output' — it does not disclose default behavior for omitted event, pagination limits, or the meaning of include_raw. This is insufficient for a tool with no annotation safety/behavior metadata.
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 short sentence, no filler, and the key verb/resource appear immediately. However, brevity sacrifices necessary detail.
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?
With three optional parameters, no annotation coverage, and no explanation of parameter semantics, the description is not adequate for selection/invocation. The presence of an output schema does not compensate for missing behavioral and parameter context.
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% and the description mentions no parameters. The phrase 'compact output' only weakly implies the include_raw toggle, and 'event' and 'limit' are left entirely to schema types/defaults.
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 ('List speakers') and the scope ('for an event'), with 'compact output' hinting at a limited response format. It does not explicitly call out sibling tools like pretalx_search_speakers or pretalx_get_speaker, so it lacks explicit differentiation.
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 list endpoint versus searching speakers or retrieving a single speaker. Context signals include many sibling tools but the description gives no exclusions 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?
With no annotations provided, the description carries the full burden of disclosing behavior. It mentions detection of overlaps and missing data, but does not state whether this is a read-only operation, whether it modifies data, what inputs it needs, or what form the output takes. The lack of behavioral context 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no superfluous words. It is well-structured and front-loaded, but it is so brief that it borders on under-specification, which is why it does not earn a perfect score.
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 tool with one optional parameter and an output schema, the description is minimally adequate. However, it omits context about the meaning of 'event' and the exact nature of 'overlaps' and 'missing data', leaving the agent to infer these from the tool name and sibling context.
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 zero description coverage, and the description does not mention the single 'event' parameter at all. There is no explanation of what 'event' refers to, whether it is required, or how its absence affects the tool's behavior. The description fails to compensate for the schema's lack of detail.
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 a specific action ('Detect') applied to schedule data, focusing on overlaps and missing data. This distinguishes it from sibling tools that retrieve or list schedule information, though it could be more explicit about what constitutes a conflict.
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. There is no mention of prerequisites, typical use cases, or when other schedule-related tools (like pretalx_get_schedule) 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'List submissions... with optional server-side filters', which largely restates the schema. No details on pagination, event identifier format, filtering behavior, rate limits, or required permissions are provided.
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, front-loaded with the action and resource. It is appropriately concise with zero wasted words, though the brevity comes at the cost of substantive explanation.
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 annotations and no schema descriptions, and despite the presence of an output schema, the description is too sparse. It does not explain how to specify an event, valid values for limit/state/track, what include_raw does, or how this listing relates to search_submissions, leaving significant gaps for an 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?
Schema description coverage is 0%, so the description must compensate. The phrase 'optional server-side filters' is generic and does not explain any of the six parameters (event, limit, state, track, include_raw, submission_type) or their intended formats, restrictions, or interactions.
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 uses a specific verb 'List' and resource 'submissions', scoped to 'an event', making the primary action clear. It hints at server-side filters but does not explicitly differentiate from sibling tools like pretalx_search_submissions, which could be a near-identical use case.
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 pretalx_search_submissions or pretalx_get_submission. There is no mention of prerequisites, exclusions, or scenarios where a different 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals a two-phase approach (server-side query plus local matching) but does not explain what 'local matching' entails, whether the operation is read-only, or any other side effects. This is insufficient for a 7-parameter tool.
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 with no fluff, but it is under-specified for a tool with 7 parameters. It is concise but not appropriately sized, lacking structural breakdown of behavior or parameters.
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, so return values do not need description. However, the operation is contextually incomplete: there are no parameter descriptions, no annotation safety signals, and the core behavior ('local matching') is undefined. This leaves significant gaps for an agent to use the tool correctly.
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 does not compensate. It only vaguely mentions 'server-side q', which likely maps to the 'query' parameter, but offers no semantics for the other six parameters (event, limit, state, track, include_raw, submission_type).
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 identifies the tool as searching submissions, with the specific mechanism of 'server-side q plus local matching'. This distinguishes it from listing or retrieving individual submissions, though it does not explicitly reference sibling tools.
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 is for searching submissions, which gives a basic usage context. However, it provides no explicit guidance on when to choose it over pretalx_list_submissions or pretalx_search_speakers, nor any 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?
There are no annotations, so the description carries the full burden. It discloses that submissions are grouped by a selected attribute, but does not explain what the summary contains, how the event parameter affects scope, or any output/edge-case behavior.
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 concise sentence with no wasted words, front-loading the primary action. It is appropriately sized for the limited information it conveys.
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?
For a tool with two parameters, an output schema, and no annotations, the description is too incomplete: it fails to explain the event parameter, valid group_by values, or the structure of the summary output, leaving the agent to guess.
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 explain the parameters. It only implies that group_by is the selected attribute; the event parameter is not mentioned at all.
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 uses the specific verb 'Summarise' with the resource 'submissions' and indicates grouping by an attribute. This distinguishes it from list/search tools that return raw submissions, though it doesn't explicitly name alternatives.
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 about when to use this summarisation tool versus the sibling list/search tools. There is no mention of 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 carries the full burden of disclosing behavioral traits. It only says 'fetch and summarise', which conveys a read-only action but omits details such as what the summary includes, how include_raw affects the output, or any side effects. This is a significant transparency gap.
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 with no unnecessary words, making it easy to scan. However, it is so brief that it sacrifices informative content, though conciseness itself is not penalized.
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 lack of annotations and 0% schema coverage, the description is too sparse to provide complete context. It does not clarify how this tool relates to sibling tools like pretalx_list_schedule_sessions or pretalx_find_schedule_conflicts, nor does it explain parameter effects. The existence of an output schema is acknowledged, but the description still leaves critical 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%, and the description mentions neither 'event' nor 'include_raw'. It fails to explain what 'event' refers to (e.g., an event slug) or the purpose and effect of 'include_raw'. The description adds no semantic meaning beyond the schema's types and defaults.
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 'Fetch and summarise the current schedule for an event' uses a specific verb and resource, clearly indicating the tool's primary function. The word 'summarise' distinguishes it from sibling tools like pretalx_list_schedule_sessions, which likely provides raw session listings.
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 a summary of the schedule is needed, but it does not explicitly state when to use this tool over alternatives or mention any exclusions. No reference to sibling tools or context is provided, leaving the agent to infer the appropriate use case.
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 present, so the description must carry the behavioral transparency burden. It only states the action and context, but does not disclose error behavior, security requirements, or any side effects (likely none). The description adds minimal behavioral context beyond the existence of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundant wording. It efficiently states the tool's core purpose.
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?
While an output schema exists, the description still lacks essential context about parameter usage, prerequisites, and the meaning of 'submission context'. The tool has three optional parameters with no guidance, making it incomplete for a new 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%, and the description does not compensate by explaining the 'event', 'speaker', or 'include_raw' parameters. An agent would have to guess what these fields mean and how they relate to the fetch, which is a severe 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 uses a specific verb ('Fetch') and resource ('one speaker profile') and adds a distinguishing feature ('with submission context'), which clearly separates it from sibling tools like list_speakers and search_speakers.
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 purpose implies a targeted single-speaker fetch, but the description does not explicitly state when to use this tool versus alternatives like pretalx_search_speakers or pretalx_list_speakers. Usage is implied rather than explicitly guided.
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 carries the full burden for behavioral transparency. 'Fetch full details' indicates a read operation, but it does not disclose whether the response includes all fields (e.g., reviews, raw data) or what 'full' means relative to the include_raw parameter. No mention of permissions, error behavior, or side effects.
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, front-loaded sentence with no filler words. Every word is useful, and it immediately conveys the core purpose without unnecessary detail.
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 three optional parameters, no annotations, and no parameter descriptions, the description is insufficient. It does not explain how to specify which submission, what the event parameter is for, or how include_raw affects the response. The absence of any usage prerequisite makes the tool hard to invoke correctly in context.
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 zero parameter descriptions and the description adds no meaning to any of the three parameters (event, include_raw, submission_code). There is no hint that submission_code identifies the target or that include_raw modifies the payload, leaving the agent completely unguided on how to fill 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 uses the specific verb 'Fetch' with the resource 'full details for one submission,' clearly distinguishing this from sibling tools that list or search submissions. It's one precise sentence that leaves no ambiguity about the tool's function.
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 when a single submission's full details are needed, but it does not explicitly state when to use this tool instead of pretalx_list_submissions or pretalx_search_submissions. No alternatives or exclusions are mentioned, so the guidance is only 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 must fully disclose behavior. It merely restates the tool's function without explaining what 'review coverage' entails, how data is aggregated, or any side effects or limitations. For a read-only summarization tool, it does not confirm safety or describe output characteristics beyond the name.
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, clear sentence with no redundant words. It is front-loaded with the main verb and resource, making it easy to scan. Every word contributes to the core meaning.
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 an output schema, so return values need not be detailed, but the description leaves critical gaps: what exactly is 'review coverage'? Does the tool require an event? What happens if 'event' is null? Given the sibling tools, the description does not provide enough context for an agent to decide whether this is the right tool or how to invoke it correctly.
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 a single parameter 'event' with 0% description coverage. The description mentions 'for an event' but fails to clarify the parameter's format, meaning when null, or whether it's required. Since the schema does not provide descriptions, the description should compensate but does not.
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 uses a specific verb ('Summarise') and identifies the exact resource ('review coverage and score trends') and scope ('for an event'). It clearly distinguishes from sibling tools like pretalx_get_submission_reviews (which retrieves raw reviews) and pretalx_summarise_submissions (which summarizes submissions, not review coverage).
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 for event-level analysis but provides no explicit guidance on when to choose this tool over alternatives such as pretalx_get_submission_reviews or pretalx_summarise_submissions. There is no mention of scenarios where this tool is preferred or not recommended.
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 one behavioral trait: graceful degradation when reviews are unavailable. However, with no annotations and no other details, important aspects like error handling, authentication needs, or return behavior remain undisclosed.
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 concisely captures the core purpose and a key behavior, 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?
For a tool with three parameters and no annotations, the description is too bare. It fails to clarify which parameters are needed for 'one submission' or what 'degrade gracefully' entails, making the tool under-specified.
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 description provides no information about the parameters event, include_raw, or submission_code. Schema description coverage is 0%, so the description does not compensate, leaving the agent without guidance on how to call the tool.
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 reviews for a single submission, using a specific verb and resource. It distinguishes from sibling tools like pretalx_get_submission and pretalx_review_summary.
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 phrasing 'for one submission' implies the appropriate use case, but alternatives and exclusions are not explicitly mentioned. It provides clear context without contrasting against sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses a behavioral trait: searches happen server-side for name/email and locally for bio/submission titles, implying a hybrid search strategy. However, it does not mention side effects, rate limits, authentication, or whether the operation is read-only. The description adds some value but lacks depth expected for a tool without annotations.
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?
One concise sentence that is front-loaded with the action and scope. No redundant phrasing, every word adds value. It efficiently conveys the core function and search method.
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 is minimal and leaves gaps. It does not explain how to use the parameters (e.g., event filtering, limit, include_raw), nor the return behavior. The output schema exists but does not cover all operational context, such as the practical implications of 'local' search. A more complete description would mention parameter usage and result format.
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%, and the description does not explain the parameters (event, limit, query, include_raw). It implicitly hints that 'query' relates to name/email and bio/submission titles, but provides no meaning for the other three parameters. The description fails to compensate for the lack of schema documentation.
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 searches speakers, and specifies search keys (name/email, bio/submission titles) and the search mechanism (server-side vs local). This distinguishes it from siblings like pretalx_list_speakers (which lists all) and pretalx_search_submissions (which searches submissions).
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 context on when to use this tool (for searching speakers) and hints at the two-phase approach, but does not explicitly mention alternatives or when not to use it. The context is clear enough for a user to infer its purpose relative to siblings, but lacks explicit exclusions.
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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