torneo
Server Details
Observatory operated and funded by devlo: real tools on frozen tasks; intervals, cost, limits.
- Status
- Healthy
- Uptime
- 100.0% over 43 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 8 tools
Several tools have overlapping advisory/request semantics: request_tournament, submit_need, and get_need all circle the same need.v1 workflow, and get_results vs get_run vs get_auto_tournament are similar snapshot readers. Descriptions do differentiate (advisory vs canonical, pre-registered vs automatic), but an agent must read carefully to pick correctly.
Mostly consistent verb_noun snake_case (get_need, get_run, get_results, list_categories, request_tournament, submit_need, explain_limits). get_auto_tournament is a noun-ish outlier, but overall readable and predictable.
Eight tools is well-scoped for a read-mostly tournament evidence server, and each tool covers a distinct surface (discovery, requests, canonical results, limits). No obvious bloat or missing filler.
Covers discovery (list_categories), request logging (submit_need/request_tournament), and retrieval (get_need/get_run/get_results/get_auto_tournament), plus rules (explain_limits). However there is no explicit tool for retrieving a specific need's publication status beyond get_need, and no cancel/update operation, leaving noticeable lifecycle gaps.
Available Tools
8 toolsexplain_limitsCInspect
Limits, freshness, conflicts and answer rule of a category or run. Read before citing evidence.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | No | ||
| category | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It signals read-only intent indirectly ('read before citing evidence') and names what it surfaces, but says nothing about error behavior, what happens if both or neither optional parameter is supplied, or the shape of the returned metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with no filler; the payload enumeration leads and the usage cue follows. It is efficient, though the telegraphic noun-phrase style borders on under-specification rather than tight writing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A metadata-inspection tool with no annotations, no output schema, and fully undocumented parameters needs the description to explain invocation semantics, especially the both-optional parameter combination. The entry covers what it exposes but leaves how to call it correctly unresolved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and neither parameter is documented in the schema. The phrase 'of a category or run' loosely maps to the two parameters, but the description never explains their semantics, that both are optional, or how they interact. It adds only marginal meaning over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the resource and the specific payload it returns (limits, freshness, conflicts, answer rule) for a category or run, which is more informative than a bare name. However, it is a noun phrase with no verb, and it never distinguishes itself from siblings like get_run or get_results that also concern runs. Purpose is implied rather than stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Read before citing evidence' is a genuine usage cue that tells the agent when this tool belongs in a workflow. But it gives no alternative, no when-not condition, and no guidance for the category-vs-run choice the two parameters imply.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_auto_tournamentCInspect
Published snapshot of automatic attempts, including failures. No execution is triggered.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | No | ||
| category | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses that the result is a published snapshot, includes failures, and does not trigger execution, but omits auth needs, freshness, pagination, and error behavior for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core purpose; the second sentence earns its place by clarifying that no execution occurs. Brevity is appropriate, though it borders on under-specification rather than being wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and 0% parameter description coverage, the description is too thin for a two-parameter retrieval tool. It leaves the agent without required category semantics and without knowing what the snapshot contains or how run_id scopes it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description never mentions either parameter. It fails to explain what category or run_id mean, whether run_id is optional, or how the two interact, adding no semantic value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
It names a resource ('automatic attempts') and notes that failures are included, but lacks a clear retrieval verb and does not distinguish itself from siblings such as get_results or get_run. An agent can guess this is a read-only snapshot, but the exact scope remains underspecified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Only 'No execution is triggered' hints at read-only use; there is no explicit when-to-use guidance, prerequisite, or comparison to alternatives such as request_tournament or get_results. The routing decision is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_needCInspect
Follow need-id in the durable published snapshot. Unknown means partial, not refused. State publication is asynchronous.
| Name | Required | Description | Default |
|---|---|---|---|
| need_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It usefully discloses that state publication is asynchronous and that an unknown need means a partial result rather than a refusal, but it omits other important behavior such as read-only nature, error conditions, and return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loads the need-id lookup, and appends two compact clarifications. No sentence is wasted, though the telegraphic phrasing makes some meaning harder to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with no output schema and no annotations, the description should explain what is returned and what a need represents. It only notes asynchronous publication and unknown-result semantics, leaving the agent without enough context to interpret the result correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate by explaining the need_id parameter. It only repeats the parameter name in 'Follow need-id' and adds no meaning about format, origin, or expected values beyond the schema's regex pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description says to 'Follow need-id in the durable published snapshot,' which restates the tool name without clearly stating that it retrieves a need. It does not explain what a need is or distinguish this lookup from sibling tools like get_run or get_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use get_need versus alternatives such as get_run, get_results, or submit_need. The statements about unknown values and asynchronous publication are interpretive notes, not usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_resultsCInspect
Canonical evidence for a category. Cite observed_at, uncertainty and limits; never the best tool. INSUFFICIENT_EVIDENCE is not a ranking.
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does add real behavioral color: the output carries observed_at, uncertainty and limits fields, and can return an INSUFFICIENT_EVIDENCE state that is not a ranking. It still omits read-only/permission expectations, error behavior, and return shape, so it is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no padding, and the resource statement is front-loaded ahead of the citation advice. However, the brevity comes at the cost of obscurity rather than efficiency — the second sentence mixes usage rules with output interpretation in a dense fragment.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description's mention of observed_at, uncertainty, limits, and INSUFFICIENT_EVIDENCE is genuinely needed and partially fills the gap. Missing are the overall return structure, category discovery, and any relation to sibling tools, leaving the definition only minimally complete for a 1-param retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 for the required "category" parameter, and it does not explain valid category values, the slug format, or how to discover them (e.g., via list_categories). It only implicitly ties the input to "a category," which is already evident from the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
"Canonical evidence for a category" names a resource and its scope (a category), so the agent knows it retrieves evidence-like output rather than, say, submitting a need. But the phrasing is cryptic jargon — it never says these are results/rankings/scores — and it draws no boundary against siblings such as get_run or explain_limits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only directive is about how to cite the output ("Cite observed_at, uncertainty and limits; never the best tool"), not when to call this tool versus the alternatives. There is no when-to-use, no precondition, and no named alternative among the seven siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_runDInspect
Canonical result bundle or explicit PRE_REGISTERED state. Unknown cost is null / UNKNOWN.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. The only disclosure is a return-value detail ('unknown cost is null / UNKNOWN'); nothing is said about read-only safety, side effects, errors, or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is short but telegraphic and jargon-laden, achieving brevity by omitting the essential action rather than by eliminating waste. The fragment is not front-loaded with the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and an undocumented required parameter, the description must do more. It leaves the agent without the action, prerequisites, or return shape needed to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the single required run_id parameter has only a regex pattern with no prose. The description adds no meaning about what run_id is or where to obtain it, so it fails to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a noun-phrase fragment ('Canonical result bundle or explicit PRE_REGISTERED state') rather than a verb+resource statement, so it never actually says what get_run does. It hints at the returned payload but an agent cannot confidently distinguish it from sibling get_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use, when-not-to-use, or alternative guidance at all. Siblings like get_results and get_auto_tournament are not referenced, leaving selection entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesBInspect
Discover categories with dated status and fixture flags. Fixtures are synthetic, never real evidence.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does add real value by disclosing data provenance — fixtures are synthetic and never real evidence — which prevents an agent from treating fixture rows as fact. It still omits the read-only nature, ordering, pagination, and result shape, so the disclosure is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no padding, and the functional statement is front-loaded ahead of the caveat. The terms used are underexplained rather than verbose, so structure is fine but the phrasing could be sharper.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no annotations and no output schema, the description should at least sketch the returned shape and the meaning of 'fixture flags'. It gestures at two returned fields but leaves 'dated status', ordering, and completeness unaddressed, leaving the agent guessing about the payload.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the rubric the baseline is 4. The description correctly implies a parameterless enumerate operation and adds no misleading argument hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a verb ('Discover') and resource ('categories') and names two attributes returned (dated status, fixture flags), so the basic intent is inferable. However, 'dated status' and 'fixture flags' are idiosyncratic internal terms that are never defined, so an agent cannot fully predict what a category is. It also does no work to distinguish this from the tournament/need/run siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to call this tool, no prerequisites, and no reference to any alternative sibling tool. The only guidance-adjacent content is the fixture caveat, which is about data meaning rather than when-to-use. An agent must infer usage purely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_tournamentAInspect
Request a tournament using need.v1. Advisory only; never starts a run or spends. Follow the returned id with get_need.
| Name | Required | Description | Default |
|---|---|---|---|
| need | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it does disclose the most important trait: this is non-executing and non-spending ('Advisory only; never starts a run or spends'). It also reveals the return contract (an id) despite there being no output schema. It omits auth requirements, error behavior, and whether requests are persisted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each earning its place: what it does, its safety posture, and the required follow-up call. The safety constraint is front-loaded and nothing is padded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It compensates well for the missing output schema by naming the returned id and the follow-up tool, and it covers the non-execution semantics. It does not help the agent populate the rich, required 'need' payload, which is the main remaining gap for a tool whose only argument is that object.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the single 'need' parameter is a deeply nested object with many enum-constrained fields (requester.kind, adaptation.kind, priorities, constraints). The description only names the schema version ('need.v1') and adds no meaning to any of these fields, leaving the schema to do all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('Request a tournament') and names the contract ('need.v1'), so the operation is unambiguous. It does not differentiate itself from the similarly named sibling submit_need or explain how it relates to get_auto_tournament, so an agent must infer the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Advisory only; never starts a run or spends' implies the context in which this is appropriate, and 'Follow the returned id with get_need' gives the next step. However, it never states when to prefer this over submit_need or get_auto_tournament, so the routing decision is left implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_needCInspect
Log an advisory need.v1 request. Do not include personal or secret data. Returns need-id; persistence is partial until private ingestion and publication.
| Name | Required | Description | Default |
|---|---|---|---|
| need | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it does disclose two non-obvious traits: it returns a need-id, and persistence is 'partial until private ingestion and publication.' The privacy warning is also useful. It omits idempotency, whether the submission is binding or purely advisory in effect, and any auth/rate-limit context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences with the action front-loaded and no filler. It is terse rather than padded, though the 'advisory need.v1' phrasing is dense jargon that a first-time caller may not parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool wrapping a complex nested payload with zero schema descriptions and no output schema, the definition leaves major gaps: what a 'need' represents, how it differs from a tournament request, and what fields like requester.kind or priorities actually control. The return value mention is helpful but far from sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for a deeply nested 'need' object with required sub-fields (requester, task_class, schema const) and constrained values (priority 0-1 weights, task_class pattern, latency/cost constraints). The description adds only the schema version name and a sensitivity warning; it explains none of the nested field meanings, so the agent must infer them from raw types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a concrete verb and resource: 'Log an advisory need.v1 request.' That is a clear action on an identifiable object and pairs sensibly with the sibling get_need. It stops short of distinguishing itself from request_tournament, the other write-style sibling, leaving the agent to infer the boundary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when this tool should be invoked versus get_need or request_tournament, and no listed preconditions. The 'Do not include personal or secret data' line is a data-handling constraint, not usage guidance. The agent must guess the intended entry point of the workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
- Changed
explain_limits5 fields changed- added
Input schema / additionalPropertiesAdded value: +false - removed
Input schema / properties / category / descriptionRemoved value: -"Category id" - added
Input schema / properties / category / patternAdded value: +"^[a-z0-9][a-z0-9-]{1,63}$" - removed
Input schema / properties / run_id / descriptionRemoved value: -"Run id (alternative to category)" - added
Input schema / properties / run_id / patternAdded value: +"^[A-Z0-9][A-Z0-9-]{1,63}$"
- Added
get_auto_tournament - Added
get_need - Changed
get_results3 fields changed- added
Input schema / additionalPropertiesAdded value: +false - removed
Input schema / properties / category / descriptionRemoved value: -"Category id, e.g. 'transcription' (see list_categories)" - added
Input schema / properties / category / patternAdded value: +"^[a-z0-9][a-z0-9-]{1,63}$"
- Changed
get_run3 fields changed- added
Input schema / additionalPropertiesAdded value: +false - removed
Input schema / properties / run_id / descriptionRemoved value: -"Run id, e.g. 'TRANSCRIPTION-001' (see list_categories, field run_id)" - added
Input schema / properties / run_id / patternAdded value: +"^[A-Z0-9][A-Z0-9-]{1,63}$"
- Changed
list_categories1 field changed- added
Input schema / additionalPropertiesAdded value: +false
- Added
request_tournament - Added
submit_need
4 tool updates
- First observed
explain_limits - First observed
get_results - First observed
get_run - First observed
list_categories
Related MCP Connectors
Observational astronomy in one place
Orbital data center & space AI compute tracker MCP: projects, launches, orbits, alerts. 100 free/day
- FixterOAuthdev.fixter
Monitoring for small teams. Logs, traces, metrics, live issue tracking, API/MCP uptime.
ADHD-friendly tasks, notes & projects for LucidNest - 18 tools, scoped tokens, Streamable HTTP.
Related MCP Servers
- AlicenseAqualityBmaintenanceReal-time cost observability for Model Context Protocol tool calls. Wraps any MCP server, attributesspend per tool/project/customer. Free 25K calls/month. EU-hosted, GDPR-ready, MIT.674MIT
- AlicenseNot gradedqualityDmaintenanceA hosted remote MCP server that lets your AI agent schedule tasks for later — reminders, delayed webhook callbacks, and recurring jobs. Read-only by design.0MIT
- AlicenseNot gradedqualityBmaintenanceEnables monitoring of running agent loops with token and monetary cost estimation, pruning of verbose thinking chains near limits, and routing sub-tasks between fast/cheap and deep reasoning models. It provides deterministic, MCP-compatible budget optimization for autonomous agents and copilot frameworks.7MIT
- FlicenseNot gradedqualityDmaintenancePassword-protected dashboard and Remote MCP observer for Codex work, recording concise task milestones via observe_start, observe_report, and observe_finish tools.-
Glama MCP Gateway
Add one secure layer between your agents and this server.