Speakeroo speaking coach

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

Goes well beyond the readOnly/openWorld annotations: discloses rate limits (1/day per network, up to 3 failed-side tries), the audio-deletion data-retention guarantee, input size/format constraints, and the exact ceiling on duration/word count. This is the kind of operational context annotations cannot carry.

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 sentences, front-loaded with the superset-value proposition, then limits, then input modes, then billing/data policy. Slightly list-like in the metric enumeration but every clause earns its place; 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?

Given a 5-param, 0-required tool with an output schema already covering return values, the description supplies everything else an agent needs: scope vs. sibling, input constraints, rate policy, data retention. Nothing material is left to inference.

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 schema already documents topic, context, audioUrl, mimeType and audioBase64. The description adds the either/or input rule ('Pass audioUrl or audioBase64') which is redundant with the schema, and no extra syntax or format hints. Baseline 3 applies when the schema does the heavy lifting.

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 ('Analyze a spoken recording') and distinguishes itself from sibling analyze_transcript by explicitly describing the superset relationship: 'returns everything analyze_transcript does plus delivery metrics only audio can give.' An agent can pick between the two immediately.

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?

Provides explicit hard limits (120s, 10MB, formats, minimum 30 words) and the free-tier rate policy, which effectively tell an agent when this tool is viable. However, it doesn't explicitly route a transcript-only caller to analyze_transcript or explain when to prefer one input method (audioUrl vs audioBase64) over the other.

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 only declare readOnlyHint and openWorldHint; the description goes well beyond them by disclosing the rate limit (5 text analyses/day per network), the fact that the quota is shared with refine_transcript, and the modality limits of text input. Those are operational constraints an agent cannot learn from 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 is front-loaded and every sentence adds routing value, but the middle clause enumerating return values (weak/filler words, rhetorical devices, scores, word-level issues) is largely redundant because an output schema exists. Slightly long, though still dense rather than 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?

For a 3-parameter read-only analysis tool with an output schema, the description covers what an agent needs: input bounds, modality limits, the alternative for audio, and quota constraints. Nothing material is left for the agent to guess.

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 all three parameters are documented in the schema (topic, context enum with default, transcript with word range), so the schema carries the load. The description restates only the transcript length, adding nothing about topic or context calibration beyond what the schema says — 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?

"Coach a speech from its text" names a specific verb and resource, and the description immediately scopes the tool to text input as opposed to audio. It explicitly contrasts itself with the sibling analyze_speech, so an agent can route 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?

States the input window (30-1500 words), states a hard limitation (text cannot show pace, pauses, pitch or pronunciation), and names the alternative tool plus the condition for choosing it. It also discloses the free tier and the shared 5/day quota with refine_transcript, which affects which tool an agent should pick.

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=true and openWorldHint=false, so safety is covered. The description adds useful behavioral context beyond that: the rubric has a descriptor for every level and the tool links to a page with a CSV download, telling the agent what it is really receiving.

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, front-loaded with what the rubric is, then its contents, then the download link and the sibling contrast. Every sentence carries information; 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?

With no parameters, an output schema present, and read-only annotations, the description does the semantic work of locating this rubric relative to the analysis tools' own rubric. It is complete for invocation, though it could note whether the returned link/CSV is the primary deliverable.

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?

There are zero parameters, so there is no parameter meaning to add; the baseline of 4 applies. The description correctly refrains from inventing argument semantics.

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?

Names a specific resource (a four-level speaking rubric) and enumerates the exact dimensions it covers (fluency, pronunciation, vocabulary range, task completion), so the agent knows precisely what it will get. It also explicitly distinguishes this rubric from the scoring rubric used by analyze_transcript and analyze_speech.

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 frames this as the teacher-facing homework rubric and contrasts it with the 1-10 scoring rubric used by the analyze_* siblings, which steers selection correctly. It stops short of an explicit 'use this when…' rule, so it falls just below full routing guidance.

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=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely new traits: results are 'random', each result carries a link to the full list on speakeroo.app, and topics open a timed practice session downstream — context not derivable from the annotations.

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 tight sentences with the purpose front-loaded ahead of the downstream link behaviour. The trailing clause about the timed practice session leans slightly promotional, but it still carries information and the whole definition is short.

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 two-parameter, read-only tool with an output schema, this covers what the agent needs: what comes back, that results are random, and that the category enum maps to recognisable exam/practice types. The un-documented 'count' parameter is the only material omission.

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 50%: 'count' is documented in-schema but 'category' has no description. The prose partially compensates by spelling out the enum members in human terms ('IELTS Speaking Part 1 questions or Part 2 cue cards'), clarifying ielts_part_1/ielts_part_2, though it says nothing about the count parameter or its 25 cap.

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 ('random speech topics') and enumerates the six category types returned, which immediately distinguishes it from the analytics-flavoured siblings (analyze_speech, refine_transcript). It stops short of naming which sibling to avoid, but the purpose is unmistakable.

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 by 'to practise with' — the agent can infer this is the tool for practising/coming up with speaking topics, but there is no explicit when-to-use, prerequisite, or alternative named. Since no sibling offers topic retrieval, the omission is low-risk but still a gap.

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=true and openWorldHint=false, so the safety profile is covered, but the description adds substantive context by disclosing the guide's contents (IPA, respelling, stress marking, tips, common-mistake note, examples) and the coverage limitation that only words Speakeroo has a guide for will work. It stops short of noting auth, rate limits, or error behavior for uncovered words.

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 purpose before the content enumeration. The second sentence is a fragment ('Links to the guide, where you can record yourself...') and the six-item contents list is dense, but every item is informative rather than 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?

An output schema exists, so return-value explanation is technically optional, and the description's added enumeration is a bonus rather than a necessity. For a one-parameter read-only lookup, the coverage caveat plus content preview is enough for an agent to call it correctly; only failure/not-found behavior is left unstated.

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 the single 'word' parameter, so the description has to carry some of the burden; it does convey that the input is a single English word (an implicit language constraint not encoded in the schema). It adds nothing about format, length limits, or handling of multi-word phrases, so the compensation is only partial.

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 verb and resource (fetch a pronunciation guide for an English word) and immediately enumerates what the guide contains, so an agent knows exactly what comes back. It is trivially distinguishable from every sibling, which are all speech-analysis/transcript tools, not word lookups.

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 phrase 'an English word Speakeroo has a guide for' implicitly states a precondition (coverage-limited lookup) and the closing line hints at a follow-on recording/check action. However, there is no explicit when-to-use versus when-not, and no named alternative for words outside the guide's coverage.

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=true and openWorldHint=false, so safety is covered and the bar is lower. The description usefully discloses that the payload includes grouped words, remediation steps, and an external link to speakeroo.app, though it doesn't clarify whether the link is fetched or merely returned as a URL string (with openWorldHint=false, that distinction matters mildly).

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, content first and the promotional link detail last. No filler and nothing repeated from the title or schema.

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?

An output schema exists, so return-value shape need not be explained, and for a zero-parameter static reference tool the description covers what the agent needs. The only soft spot is the unmentioned relationship to sibling speech-analysis tools, which is a usage-guidance issue more than a completeness one.

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 and the schema is 100% covered, so there is nothing for the description to disambiguate. The baseline of 4 applies for a no-argument tool.

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 specific resource — common filler words in spoken English, grouped by function, plus steps to stop using them — which is concrete and clearly distinct from any sibling (none of analyze_speech, refine_transcript, etc. serve static reference content). It never uses an explicit verb like 'lists' or 'returns', so the agent must infer that the tool is a static lookup, but the content is specific enough to select it confidently.

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 guidance, no mention of sibling tools, and no stated trigger for this over analyze_speech or refine_transcript. The agent is left to infer that this is the reference-content option when a user asks about filler words.

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 a safe read-only, closed-world operation, so the description's extra context is a bonus: it discloses the 30-1500 word input bound and, importantly, that this tool consumes the same daily text allowance as analyze_transcript (a rate/quota constraint not visible in annotations or schema). It does not describe failure behavior when the quota is exhausted.

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 tight sentences, each earning its place: purpose with structure names, then return contents, then input bound and quota note. The rewrite purpose is front-loaded with zero preamble.

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 an output schema present, spelling out the returned sections/score/summary/tip is mildly redundant but reassuring, and the quota-sharing note plus word range cover the practical call requirements. Only the quota-exhaustion behavior is left unspecified, which is a minor gap for a read-only 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 100% and all three parameters are documented in-schema (topic example, context enum, transcript word range), so the schema carries the semantics. The description repeats the 30-1500 word bound but adds nothing about how 'topic' or 'context' shape the rewrite — the correct baseline of 3 when the schema does the heavy lifting.

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 verb ('Rewrite') plus the resource ('a speech') and enumerates concrete target structures (PREP, STAR, problem-solution, rule of three). It is unmistakably distinct from sibling 'analyze_transcript' — this one restructures, that one analyzes — and even names that sibling when discussing the shared quota.

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?

'Chosen to fit it' and the input word range imply when the tool applies, and the note about sharing the daily allowance with analyze_transcript hints at a usage constraint. But there is no explicit when-to-use/when-not guidance versus analyze_speech or analyze_transcript — the agent must infer that restructuring is a different intent from analysis.

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