Prorakel · Fußball-Prognosen

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the safe read-only, idempotent, closed-world profile, so the description's real contribution is scope disclosure: it states that UNFLATTERING results (predictions that missed) are included, which is exactly the kind of thing an agent should not have to discover empirically. It also discloses the shape of what comes back (totals, recent days, per competition, with match counts) — valuable since there is no 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the subject ('Die öffentliche Trefferbilanz von Prorakel') and then layers scope, evaluation timing, inclusivity of misses, and the three breakdowns. No filler, though the sentence is long enough that splitting the breakdown list would improve scanability.

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 zero required parameters, no output schema, and annotations covering the safety profile, the remaining burden is telling the agent what data it will get — and the description does so (overall values, last days, per competition, match counts). Only the time window implied by 'die letzten Tage' stays vague.

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 coverage is 100% and the single optional parameter 'wettbewerb' is fully documented in the schema, including the note that the overall figure is always returned. The description's phrase 'je Wettbewerb, jeweils mit der Zahl der Spiele' reinforces what the competition dimension yields but adds no syntax or behavior beyond the schema. Baseline 3 applies.

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 a specific artifact — the public hit/miss balance of Prorakel's predictions, evaluated after the final whistle, including wrong ones — and enumerates the breakdowns (overall, last days, per competition). That clearly separates it from sibling tools that list matches (spiele_am_tag, spieltag) or competitions (wettbewerbe), though no sibling is named explicitly.

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?

Usage is only implied: the mention of 'je Wettbewerb' hints that the optional competition filter narrows a per-league view, but there is no explicit statement of when to call this instead of a sibling tool or of any prerequisites. Nothing is misleading, but an agent must infer the choice itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the read-only/idempotent/closed-world profile, and the description adds real context beyond them: the projections come from 10,000 simulated remaining seasons and are refreshed after every matchday. It stops short of describing the returned data shape, which keeps it from a 5.

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?

A single front-loaded sentence that names the outcome categories first, then the competitions, then the methodology. No filler.

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 one required enum and full annotation coverage, the description supplies enough to call it correctly and understand the modelling basis. The absence of an output schema means the result format is unstated, which is the only meaningful gap.

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 100% with a single enum, so the schema already does the work. The description maps the three league names onto the enum values but adds no syntax or format detail beyond that, making the baseline 3 correct.

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 resource (Chancen jedes Klubs auf Tabellenbereiche am Saisonende) with the exact outcome categories and leagues covered. An agent can distinguish this projection tool from siblings like bilanz or spieltag purely from the description.

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?

Usage is implied — you call it to get season-end probability projections, and the note that it is recalculated after each matchday hints at freshness — but there is no explicit when-to-use, when-not, or pointer to an alternative such as bilanz for actual results.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavior: predictions are free for three games per day but subscription-gated otherwise, and tendency data appears only after the final whistle — context an agent cannot get from the structured fields.

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?

Purpose and scope are front-loaded, followed by return fields and the prediction/subscription nuance. The subscription detail is slightly tangential but still earns its place by setting expectations about what data appears per game.

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 output schema, the description carries the burden of explaining return values, and it does: kickoff, live score, final result, post-match tendency, and probability fields. Date range constraints live in the schema, so nothing critical is missing.

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 coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by clarifying that the date is interpreted in German time (deutsche Zeit) and that the competition filter selects 'one' versus 'all' competitions.

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 first sentence states a specific verb and resource (all games of a calendar day, across all competitions or one) and enumerates the returned fields (kickoff, live score, final result). It does not explicitly name the sibling spieltag or bilanz to differentiate, but the 'calendar day' scope is concrete enough for an agent to distinguish it.

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?

Usage is implied: query this when you want the games of a specific date, optionally filtered to one competition. It never states exclusions or points to spieltag/bilanz as the alternative for other views, so the agent must infer the boundary itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, non-destructive, and closed-world behavior. The description adds meaningful data semantics beyond annotations: it returns Prorakel tendency before kickoff and final score plus whether the tendency was correct after the whistle.

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 definition is front-loaded and efficient: it states the core result first, then adds availability. The long competition list is justified as it defines scope, though it makes the sentence heavier than necessary.

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 one required parameter, rich annotations, and no output schema, the description gives enough context about what is returned and when final scores appear. It is nearly complete, though a brief note on how tendency fields are represented could help.

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 coverage is 100%, so the enum and parameter description already define the only parameter. The description lists supported competitions by name but does not map them to the enum codes, adding only moderate context beyond the 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 states a specific resource and scope: all matches of the current matchday for a competition, including Prorakel tendency and final-score behavior. It does not explicitly differentiate itself from siblings like spiele_am_tag or bilanz, so it falls short of a 5.

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?

Usage is implied by 'aktueller Spieltag' and the supported-competition list, but there is no explicit guidance on when to use this instead of spiele_am_tag or bilanz. No exclusions or prerequisites are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already establish this as a safe, read-only, idempotent lookup. The description adds useful behavioral context by clarifying that the result is the complete set of competitions and that each entry includes code, country, and type. For a zero-parameter reference list, this is sufficient.

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 main purpose front-loaded and the important usage note about the `wettbewerb` code placed second. Every sentence adds value.

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?

Given zero parameters, a simple read-only reference-list purpose, and no output schema, the description supplies exactly what an agent needs: what is returned and how the returned code is used elsewhere. Nothing material is missing.

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 has no input parameters, so the baseline is 4 and no parameter explanation is needed. The description appropriately focuses on what the entries contain instead of describing nonexistent inputs.

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 states a specific resource (all competitions predicted by Prorakel), enumerates the categories covered (leagues, cups, European cups), and names the returned fields (code, country, type). This clearly distinguishes it from the match- and standings-oriented sibling tools.

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?

It gives clear usage context by explaining that the returned code is used as `wettbewerb` in the other tools, which is exactly what an agent needs to know. It does not explicitly state when not to use it or name alternatives, but the sibling tools cover different resources rather than being direct substitutes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.