MissedTakes

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

With readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false already declared, the safety profile is covered. The description usefully adds the return ordering (newest first) and the lookup modes, but is silent on what happens with an ambiguous partial-name match (multiple or zero pundits) or how slug and name interact if both are supplied.

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 sentences, front-loaded with what is returned, followed by how to look it up. No filler, no redundancy, and the ordering behavior is packed into a clause rather than a separate sentence.

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, so the description must carry the return-value burden, and it does so reasonably: accuracy, MissedTakes Score, sample size, and the current-cycle calls. The remaining gap is resolution behavior for partial names and the unexplained overlap with the `pundit_record` sibling.

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%, so every parameter is already documented inline, which sets the baseline at 3. The description reinforces the slug-or-name lookup and the "current cycle" framing but adds no syntax, precedence rule, or format detail 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: one pundit's graded record from past cycles plus their calls in the current cycle, ordered newest first. That is clearly more than a restatement of the name. However, it never distinguishes itself from the sibling tool `pundit_record`, which sounds like it covers the same ground, so an agent still cannot confidently route between the two from the text alone.

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?

"Look up by slug, or by part of their name" gives usage context and two lookup modes, implying this is the tool for retrieving an individual pundit's record. But there is no when-to-use vs when-not guidance and no mention of when `pundit_record`, `outlet_record`, or `find_entities` would be the better choice.

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 readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuine value by disclosing result ordering ('newest first') and the shape/content of each returned call, including the pundit's graded historical record.

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?

Front-loaded with the core noun phrase and the ordering guarantee before the field enumeration, and the slug-provenance note is placed last where it is needed. The field list is dense but each item carries information; only slight tightening is possible.

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 must describe returns, and it does so adequately (per-call fields plus the pundit's graded record). Pagination (25 per page) and cycle semantics live in the schema, so leaving them out of the prose is acceptable; auth and error behavior remain unstated but are minor for a read-only listing.

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%, so raceSlug, page and cycle are documented in the schema itself; the description's note on raceSlug (election_races or the chamber:/national: forms) largely mirrors the schema text. Nothing new is added for the page or cycle parameters, so the 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?

States a specific resource (individual calls on one race/chamber) and enumerates what each call contains: speaker, timestamp, pick, excerpt, and graded record. It also names election_races as the source of the raceSlug, giving partial sibling routing, though it doesn't contrast itself against list_takes or pundit_record.

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: you call it when you want the calls on a given race, and raceSlug is sourced from election_races. There is no explicit when-not or comparison to the sibling take-listing tools that might return overlapping data.

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 bar is covered. The description adds meaningful behavior beyond that: calls counted in the last 7 days, each pundit's latest pick counted once, a forecaster/commentator split, and the VoteHub polling average — all useful operational 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?

Scoping and filtering are front-loaded, but the opening is a single sprawling run-on sentence packing in every returned field. It is information-dense rather than concise, and some output detail could be trimmed or structured.

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, so the description carries the burden of explaining return content, which it does well (pundit counts, splits, recent calls, polling average). Combined with the covered annotations, an agent has enough to invoke it correctly, though sibling differentiation remains thin.

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 75%, and the description largely repeats what the schema already documents (cycle default, office enum, two-letter state). It does convey that the office filter spans race types, but the `limit` parameter gets no description-level treatment, so value over the schema is marginal.

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 resource (races/chamber control/national House popular vote that pundits have called) and scopes it to an election cycle, which is more than a restatement of the title. However, it does not clearly contrast itself with the sibling election_race_calls, so an agent cannot fully tell them apart from the text alone.

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 current one unless you pass cycle" and "Filter by office ... or two-letter state" imply how the tool is used, and "Use it to find a race slug" hints at the purpose. There is still no explicit guidance on when to use this versus election_race_calls or election_pundit.

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, and closed-world. The description adds a real behavioral constraint beyond them: only pundits and outlets with a public page are returned, which warns an agent that some known entities will legitimately be absent. No pagination or result-shape detail, but the coverage constraint is meaningful.

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 sentences, front-loaded with the lookup purpose, followed by the call-ordering rule and the scope caveat. No filler sentences and nothing redundant.

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 small two-parameter lookup with no output schema and full annotation coverage, the description supplies purpose, required call ordering, and a scope limitation. It does not describe the returned match list (single vs multiple matches, ambiguity handling), which is a minor remaining 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% and both parameters are documented in the schema, including the enum values and the 'part of one' example. The description's 'by full or partial name' adds only marginal confirmation, so the 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?

States a specific verb (look up) and resource (the slug for a pundit, outlet, NFL team, player, or prediction type) with the accepted input (full or partial name). It also implicitly distinguishes itself from siblings by stating that the other tools take slugs, never names.

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?

Explicit call ordering: 'Call this first whenever the user names someone', plus the reason (the other tools take slugs, never names). This is a clear when-to-use rule with the alternative behavior named.

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/openWorld=false, so safety is covered. The description adds genuine behavioral context beyond that: the counting convention ('one voice per pundit, their latest call standing'), the median-margin semantics, and that the final score appears only once played.

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?

One dense sentence that front-loads the tool's purpose, followed by the same field details as the schema. It is appropriately sized for the tool's complexity, though the run-on aggregation clause is slightly heavy.

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?

No output schema exists, so the description carries the return-value burden and does list the returned aggregates (counts, median margin, per-pundit calls, final score). It is nearly complete, with only the exact response shape/pagination left implicit.

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 parameters are already documented. The description restates the week ranges (also in the schema) and clarifies that either team's slug is acceptable, a small addition but not much beyond the schema baseline.

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 ('what the pundits predicted for one NFL game') and then enumerates the exact aggregates returned (side counts, median margin, per-pundit score calls, final score). This is clearly distinct from siblings like pundit_record and leaderboard, which cover different scopes.

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 description explains how to identify the game (seasonYear, week, either team's slug) but never states when to reach for this tool over pundit_record or leaderboard. Usage is implied by the resource rather than contrasted with alternatives.

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 bar is lower. The description still adds real behavioral context: the ranking is defined by MissedTakes Score (skill vs a naive baseline), provisional records are unranked, and the ranking scope changes when a slug is supplied.

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 dense but front-loaded sentences; the identity, returned fields, and ranking caveat come before the optional parameter guidance. Every clause carries information, though the second sentence is slightly overloaded with the slug discovery hint.

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 compensates by naming the columns returned and the ranking rule, and it covers the optional parameter's purpose. An agent has enough to call this correctly and interpret the result.

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 baseline is 3, but the description goes further: it defines what a prediction type slug means conceptually ('rank within one kind of claim'), gives a concrete example (mock drafts), and routes the agent to find_entities, kind prediction_type, to discover slugs.

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 (ranked NFL pundit leaderboard) and enumerates the returned rows — MissedTakes Score, accuracy, graded takes, articles. Anchoring it to 'the same rows missedtakes.co/nfl/leaderboard prints' makes the scope unambiguous and implicitly separates it from the single-entity sibling pundit_record.

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?

Explains the one usage variation (pass a typeSlug to rank within one claim kind, e.g. mock drafts) and notes that provisional records under ten graded articles are excluded. However, it never says when to reach for this versus pundit_record, outlet_record, or list_takes, so alternative selection 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.

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 real behavioral context beyond that: the return shape, the 25-rows-per-page pagination behavior, and the grade/verdict semantics, which the agent needs to interpret results.

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 dense but well-ordered sentences: returns first, then filters, then pagination. Every clause carries information, though the verdict thresholds duplicate what the schema already states, creating slight redundancy.

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 describing returns, and it does so thoroughly (fields plus grading arithmetic). For an 11-param, all-optional filter tool with high schema coverage, this is complete enough; only explicit sibling routing 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?

With 91% schema description coverage, the schema already documents nearly every parameter. The description restates the verdict thresholds (which already appear in the verdict schema description) and clarifies that claimedAfter/claimedBefore filter on publication date, adding only marginal value over 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?

States a specific resource (individual NFL predictions) and enumerates what each take contains — pundit, date, excerpt, grade, grading arithmetic — so the agent knows exactly what is being listed. It does not explicitly contrast itself with siblings like pundit_record or leaderboard, which would be needed for 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 through the filter list and the pagination note ('pass page for more'), which tells the agent how to page. However there is no explicit when-to-use or when-to-prefer-an-alternative guidance (e.g. pundit_record for a single pundit's summary), leaving the routing decision to inference.

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, closed-world behavior, so the safety profile is covered. The description adds real value beyond them by disclosing the shape of the result — overall record, breakdown by prediction type, and contributor count.

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?

One front-loaded sentence with a colon-delimited list of the aggregate dimensions; no filler. The dependent clause 'aggregated across everyone writing or speaking under its banner' is slightly wordy but still earns its place by defining the aggregation.

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 read tool with no output schema, the description adequately conveys what comes back (overall record, per-prediction-type splits, pundit count). The main residual gap is routing guidance against the many sibling record/leaderboard tools.

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 single parameter is fully documented in the schema (outletSlug, sourced 'from find_entities'), and the description adds nothing about it. With 100% schema coverage and one param, the 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?

States a specific resource and scope: 'One publication's NFL record, aggregated across everyone writing or speaking under its banner.' The phrase 'one publication's' implicitly separates it from sibling pundit_record (one person's record), but no sibling is named explicitly, so it falls short of full differentiation.

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: an agent can infer this is the outlet-level aggregate versus pundit_record, leaderboard, or list_takes, but the description never states when to choose this tool over those alternatives or what prerequisites apply.

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 readOnlyHint, idempotentHint, destructiveHint=false and a closed-world scope, so the safety profile is covered. The description adds the payload composition (score, accuracy, sample size, type breakdown, awards), which is real behavioral context given there is no output schema, though it says nothing about permissions or fallback behavior for unknown slugs.

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?

One sentence front-loading the resource and its contents, followed by the routing clause. Every clause earns its place and nothing is repeated from the title.

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 usefully summarizes what comes back, and the single required param is fully documented by the schema while annotations carry the safety profile. Only missing element is any caveat about missing/invalid slugs.

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?

Single parameter with 100% schema description coverage; the schema already documents both the slug and its source (find_entities). The description adds no syntax or lookup guidance beyond that, so the baseline of 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?

States a specific resource (one pundit's published NFL record) and enumerates exactly what the payload contains: MissedTakes Score, accuracy/sample size, breakdown by prediction type, and awards. It also names the sibling it is not (election_pundit), so an agent can distinguish the two without opening either schema.

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?

Explicitly routes the alternative case: 'For their election record, call election_pundit.' That gives clear context for when to pick the sibling, but it never states a when-not condition for this tool itself or prerequisites beyond the slug.

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