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

With no annotations, the description carries the full burden and does well: it discloses that notes are added in a single Live undo step, that existing notes remain, that per-note validation matches add_notes_to_clip, and that pitch/velocity are clamped. It does not describe error responses or the return payload, but the mutation and undo semantics are clearly covered.

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?

Well front-loaded: purpose, then side effects, then a concrete example, then edge cases. Every section adds signal. The example line is slightly dense but earns its place by demonstrating several parameters at once.

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 7-parameter mutation tool with no annotations and no output schema, the description supplies purpose, undo behavior, a usage example, and validation/clamping edge cases. The main residual gap is per-parameter meaning, especially velocity_scale_per_repeat and transpose_per_repeat units.

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 0% across 7 parameters, so the description must compensate. The worked example illustrates track_index, clip_index, cell, cell_length, repeats, and transpose_per_repeat in positional context, but velocity_scale_per_repeat is never mentioned and no parameter's meaning is spelled out, so 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?

States a specific verb and resource: 'Repeat one note cell N times instead of sending every note.' It also references the sibling add_notes_to_clip, which helps an agent place it in the tool family. The clip-writing nature is implied rather than stated outright, so it's clear but not maximally sharp.

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 'instead of sending every note' implies the use case (write repetitive patterns compactly), and add_notes_to_clip is named as the tool whose validation applies. But there is no explicit when-to-use/when-not or a directive comparison against add_notes_to_clip, leaving the agent to infer the routing.

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?

With no annotations, the description carries the full burden and does disclose meaningful behavior: single-undo-step mutation and the crucial fact that existing notes are preserved (append, not replace). It still omits how validation failures surface and whether the clip/track must be MIDI beforehand.

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?

Four tightly packed lines: purpose first, then side effects, example, and edge cases. Every sentence adds a distinct piece of information with zero 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?

For a mutation tool with no annotations and no output schema, the description covers purpose, side effects, usage example, and failure cases well. The remaining gap is the shape of the primary 'notes' payload, whose required fields are only hinted at by a truncated example.

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 0%, so the description must compensate for all three parameters. The example partially does this by showing positional usage (track_index=0, clip_index=0, notes=[...]), but the note-object fields are elided ('...') and index meaning/range is never explained.

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 and resource ('Add validated MIDI notes') scoped to a precise target ('existing Session clip'). The word 'add' plus 'existing' implicitly separates it from create_clip, clear_clip_notes, and get_clip_notes, so an agent can route correctly without opening the 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?

Gives clear operating context ('existing Session clip') and enumerates rejection conditions (audio clips, empty slots, invalid MIDI ranges), which functions as when-not guidance. It does not, however, name the alternative sibling (e.g. add_notes_pattern) or state when that should be preferred.

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?

With no annotations, the description carries the full burden and does well: it declares the side effect (reads the file from disk), and specifies the failure contract — missing files and unsupported encodings return a structured {"ok": False, "reason": ...}. It omits anything about cost, latency, or supported formats, which is the remaining gap.

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?

Tightly structured with front-loaded purpose, then labelled Side effects, Example, and Edge cases blocks. Every sentence adds information an agent needs; 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 no output schema, the description must describe the return value, and it does list the metrics returned (LUFS-I, true-peak, RMS, per-band energy) plus the error shape. It stops short of describing result structure or units, so a little is left to discovery, but nothing critical is missing for a 1-parameter read 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 coverage is 0% and the single parameter is undocumented in the schema, so the description must compensate — and it does via the worked example path="/stems/kick.wav", which conveys that path is a local filesystem path string. Absolute-vs-relative and platform conventions are still left to inference.

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 (compute) and resource (a local audio file) plus the exact metrics produced: LUFS-I, true-peak, RMS, and per-band energy. This is far more specific than its sibling analysis tools (analyze_mix, find_frequency_masking), though it never explicitly names how it differs from them.

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: the metric list tells the agent this is for objective loudness/level measurement of a single file, and the example demonstrates the call shape. However, there is no statement of when to prefer this over analyze_mix or find_frequency_masking, and no preconditions are described.

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?

No annotations, so the description carries the full burden and does well: it discloses the disk-read side effect, the 16-stem cap error behavior, and the per-stem missing-file error shape. Missing only details on failure modes for other errors or expected runtime.

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 purpose, then side effects, example, and edge cases in four tight, information-dense blocks. No filler sentences.

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 one-parameter analysis tool with no output schema, the description covers purpose, side effects, example, and error behavior. What remains unsaid is how to interpret the returned LUFS/masking values and typical performance, but the essentials for correct invocation are present.

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 0% and there is one parameter, so the example call ('stems=[...]') and the edge-case note (>16 raises error, missing files reported per-stem) supply the semantics the schema lacks. This meaningfully compensates for the absent schema descriptions.

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 (run) and resource (per-stem analysis and pair-wise masking across local audio files), with a concrete example call. Distinguishes itself from audio tooling siblings like analyze_audio and find_frequency_masking by naming the exact outputs (LUFS, masking scores).

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 an example that implies usage (batch stems of a mix), but never explicitly says when to use this versus find_frequency_masking or analyze_audio. No exclusion criteria or prerequisite context beyond the 16-file limit.

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?

With no annotations provided, the description carries the full burden and does so well: it names the side effects (npm install, npm run build in the supplied directory), states that it never raises during subprocess execution, reports each step's returncode instead, lists host requirements, and specifies the missing-package.json error shape. This is exactly the behavioral disclosure a mutation-capable tool needs.

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 correctly, but the bulk of the description is a full restatement of the JSON return contract — including field-by-field semantics — even though an output schema already exists for this tool. That block is largely redundant and crowds out the smaller amount of information the schema cannot supply.

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 build-runner with filesystem side effects and no annotations, the description covers side effects, error modes, host prerequisites, and failure semantics well enough to invoke safely. Its only meaningful gap is the directory-path contract for project_path, which 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 description coverage is 0% for the single project_path parameter, so the schema contributes nothing. The description partially compensates — it implies the value is a project root directory ('supplied project directory', 'relative to the project root') and shows an example call — but never states whether the path must be absolute, whether it must contain package.json, or how relative paths resolve.

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 and resource: 'Run a build of an Ableton Extension project.' It is clearly a build/compile operation, distinct from the read-oriented Ableton Live siblings. However, it never names the nearest sibling (scaffold_extension) or otherwise explicitly draws the boundary between scaffolding and building, so the 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?

Usage is implied rather than stated: the example shows a direct invocation and prerequisites (Node.js and npm) are named. There is no explicit guidance on when to invoke this versus scaffold_extension, or at what point in a workflow a rebuild is warranted. Adequate but leaves sequencing 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?

With no annotations to lean on, the description carries the full burden and does so well: it discloses mutation of successful items within a single undo step (transactional scope), aggregated per-item errors that don't abort later items, and off-grid snapping reversal reported as CUE_SNAPPED_TO_GRID. This is exactly the behavioral context an agent needs for a bulk mutating call.

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, followed by clearly labeled 'Side effects' and 'Edge cases' sections and a compact example. Every sentence earns its place, though the labeled list format is slightly more verbose than a tight prose sentence would be.

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 no annotations, no output schema, and an opaque parameter, the description covers the critical behavioral unknowns (undo atomicity, error aggregation, snapping). It stops short of the full per-item field set and any return-value shape, but for a bulk mutation tool this is close to complete.

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 0% and the single 'items' param is an untyped array of objects with additionalProperties, so the schema alone is useless. The inline example [{"name": "A", "time": 0}] meaningfully reveals the item shape, though it doesn't enumerate all possible fields or types, so it compensates substantially but not completely.

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 ('create or rename') and resource ('multiple cue points') plus the batching scope ('as one command'). The word 'multiple'/'bulk' cleanly distinguishes it from the singular create_cue_point sibling without needing schema inspection.

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 batch framing implies when to use it (multiple items at once), and it notes renaming behavior. However, it never explicitly names create_cue_point as the single-item alternative or states the condition that should route an agent to one vs the other, leaving the choice 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?

No annotations are provided, so the description must carry the behavioral burden. It discloses key side effects: clears notes in one Live undo step, reports observed delta, and returns structured errors for empty/audio clips. This goes beyond schema. Missing info on permissions or exact return format, but solid.

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 purpose, then side effects and example, then edge cases. Three short sentences, no waste, well-structured. Could be slightly more concise but effective.

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 mutation tool with no annotations and no output schema, the description covers purpose, side effects, example, and edge cases. It lacks parameter definitions and return format details, but given the simplicity (2 params, no output schema), it's largely complete.

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. It provides an example ``clear_clip_notes(0, 1)`` showing track_index and clip_index usage, but does not explicitly define parameter meanings or types. The example helps but is insufficient for full semantic clarity.

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?

Specific verb+resource: 'Remove every MIDI note from one Session clip' clearly states what it does. The example clarifies it empties a MIDI clip without deleting it. However, it doesn't explicitly differentiate from sibling tools like delete_clip or add_notes_to_clip, though the MIDI note scope is distinct.

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 implies usage (empties a MIDI clip) and mentions edge cases for empty or audio clips, but does not state when to use this versus alternatives like delete_clip or add_notes_to_clip. No explicit when-not 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?

With no annotations provided, the description carries the full burden and meets it: it discloses the mutation and its one-undo-step reversibility, the LIVE_UNAVAILABLE error condition, and a subtle caveat that the 96-track TRACK_LIMIT_REACHED guard does not apply here. This is exactly the kind of behavioral context annotations would otherwise supply.

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 purpose, then side effects, examples, and edge cases in a logical order. Dense but every section earns its place; the prose is slightly terse in spots but not 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 mutation tool with no annotations and no output schema, the description covers side effects, error behavior, and track-limit nuances well. It stops short of stating what is returned or any host/permission prerequisites, but is largely complete for correct invocation.

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 0%, so the description must compensate. It partially does via examples (name='vocals' appends a named track; index=2 inserts at position 2), but it never explains the meaning of the default index=-1 or the null default for name, leaving the default/append semantics to inference.

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 and resource ('Create a new audio track in Ableton Live') and the phrase 'this audio variant' implicitly signals the existence of a MIDI counterpart. It distinguishes the tool well but never explicitly names the sibling create_midi_track, so an agent must infer the pairing.

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 examples show how to call it (name vs index) but offer no guidance on when to use an audio track versus a MIDI track or other creation tools. There is no when-to-use, when-not-to-use, or alternative-selection 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?

With no annotations, the description carries the full burden and does well: it discloses the undo footprint (one undo step), the dry_run semantics, and the failure condition. It stops short of stating permission prerequisites or what the call returns on success.

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 purpose sentence, then labeled Side effects / Example / Edge cases blocks, each earning its place. The labeled structure is slightly heavier than needed but nothing is wasted.

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 mutation tool with no annotations and no output schema, it covers side effects, undo scope, dry-run, and the key edge case. Remaining gaps are the return value and the meaning/range of track_index and clip_index, both of which the schema leaves undocumented.

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 0%, so the description must compensate, and it partially does: it explains dry_run and the example create_clip(0, 1, 4.0) implies positional order with length_beats in beats. However, track_index and clip_index semantics (what a Session slot index means, valid ranges) are never explained.

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 (Create) and resource (empty MIDI clip in an empty Session slot), including the scoping constraint that distinguishes it from siblings like add_notes_to_clip, delete_clip, or create_clip_automation. An agent can tell what this tool does without opening the 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?

Gives a clear precondition (only empty slots on MIDI tracks accept this) and explains the dry_run validation path, which tells the agent when the call will succeed or is a rehearsal. It does not name a sibling alternative for the non-empty-slot case, so it stops short of explicit routing.

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?

No annotations are provided, so the description carries the full burden and does so well. It discloses the destructive side effect ('clears and rewrites one clip envelope in one Live undo step'), the API prerequisite, a hard limit (max 500 points), error behavior (AMBIGUOUS_MATCH) with a recovery path (device_index), and semantic gotcha (stepped envelopes).

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-loads purpose in one line, then labels blocks 'Side effects:', 'Example:', 'Edge cases:'. Every sentence is load-bearing — no restated name, 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?

For a 5-param mutation tool with zero annotations, no output schema, and 0% schema coverage, the description supplies side effects, limits, errors, an example, and alternative routing. Only the return/response behavior is unspecified, which is a minor gap for a mutating write 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 coverage is 0%, so the description must compensate, and it largely does: it explains device_index's role (disambiguating a parameter name shared across devices), the automation_points format via a concrete example ({"time", "value"}), and the 500-point cap. track_index and clip_index are only shown positionally in the example, not explained, so it falls short of full coverage.

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 and resource: 'Replace one Session clip parameter envelope with verified breakpoints.' The scope (one clip, one parameter, Session clip) is precise and lets an agent distinguish it from the sibling create_clip_automation_curve 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 to the alternative for a concrete case: 'Envelopes are stepped, so a smooth ramp needs dense points — or use create_clip_automation_curve.' It also flags the Session-clip context requirement. It stops short of a full when-to-use vs when-not comparison across all automation siblings, but the key alternative is named with its selecting condition.

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?

With no annotations, the description carries the full burden and does well: it discloses the destructive side effect ('replaces one clip envelope in one Live undo step'), the server-side expansion into contiguous steps, and a hard 500-step cap with resolution as the remedy. It stops short of stating permission/auth requirements or exactly which envelope is overwritten when device_index is null.

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-loads the core action, then organizes the rest under Side effects / Example / Edge cases. Dense with useful detail and little waste; only mildly longer than strictly 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?

For a mutation tool with no annotations and no output schema, this covers side effects, undo semantics, an invocation example, and a real failure mode with its mitigation. The main gap is the unexplained device_index parameter and no statement of return behavior.

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 0% across 7 params, so the description must compensate. It clarifies control_points format (time/value objects), shape usage (shape="exp"), and resolution's role in avoiding overflow — solid for those — but never explains device_index, track_index, clip_index, or parameter_name, and lists no valid shape values.

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 and resource: 'Write a smooth envelope from a handful of control points.' An agent can tell it writes clip automation, but the description never distinguishes it from the sibling create_clip_automation or get_clip_automation, leaving the reader to infer the difference from name 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?

There is no when-to-use guidance and no mention of alternatives such as create_clip_automation or set_parameter_value. The example shows a valid call but does not say under what circumstances this tool should be preferred over its siblings.

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?

With no annotations, the description carries the full burden and largely delivers: it discloses that the Set is mutated in one undo step, that the playhead moves temporarily, and names two specific failure modes (PLAYHEAD_NOT_MOVED, CUE_SNAPPED_TO_GRID). It stops short of a 5 because it does not describe the return value or what happens if the name collides at a different time.

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-loads the purpose, then uses labeled lines ('Side effects:', 'Example:', 'Edge cases:') that make it scannable. Every sentence carries content; the only cost is that the error-code details are dense for the space they occupy.

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 mutation tool with no annotations, no output schema, and 0% schema coverage, the description covers side effects, an example, and error conditions well. It leaves out the return value and how it relates to the sibling cue-point tools, keeping it from a 5.

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 0% for two parameters, so the description must compensate. The example create_cue_point("Verse", 8.0) and the phrase 'at a beat time' imply that 'name' is a text label and 'time' is a numeric beat position, which adds real meaning, but neither parameter is explicitly defined.

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 and resource ('Create or idempotently rename a cue point at a beat time'), and the example clarifies the operation. It does not name any sibling (bulk_create_cue_points, delete_cue_point, get_locators) to differentiate itself, so it stops 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?

No explicit when-to-use or when-not guidance is given. The 'idempotently rename' phrasing implies it is safe to call repeatedly at an existing beat, which is a mild usage signal, but alternatives like bulk_create_cue_points or delete_cue_point are never referenced.

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?

With no annotations, the description carries the full behavioral burden and does well: it discloses the mutation, that it occurs in one undo step, and the concrete failure mode (TRACK_LIMIT_REACHED at >=96 tracks). It omits permission/auth context and what happens if the index is out of range, but the disclosure is well above average for a mutation 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?

Tight and front-loaded: purpose first, then labeled Side effects, Example, and Edge cases segments. Every sentence adds distinct value and none is wasted.

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 mutation tool with no annotations or output schema, the description covers mutation semantics, undo behavior, and one hard failure mode. The remaining gap is the index parameter's meaning and range, which is needed to call it correctly beyond the default path.

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 0%, so the description must compensate and only partially does. The example illustrates the name parameter, but the index parameter is entirely unexplained in both schema and description, and the default placement behavior is only hinted at by the word "appends".

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 and resource ("Create a new MIDI track") and scopes it to Ableton Live. The MIDI qualifier cleanly distinguishes it from create_audio_track and other create_* siblings without needing the 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?

Usage is implied by the purpose and the edge-case note, but there is no explicit when-to-use or when-not-to-use guidance and no reference to alternatives such as create_audio_track or create_clip. An agent must infer when this is the right tool.

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?

With no annotations, the description carries the full burden and does well: it states that deletion removes one clip in one Live undo step, which is essential for understanding reversibility, and warns that clip_index indexes Track.arrangement_clips and must be re-read after structural changes because indices shift. This is meaningful behavioral context beyond the schema. It does not mention permissions, failure modes, or what happens if the clip is referenced elsewhere, so it is strong but not exhaustive.

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 front-loaded with the core action, then organized into side effects, example, and edge cases. It is appropriately sized and each section adds value. The edge-case sentence is dense but necessary; no sentence is clearly 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?

This is a mutation tool with no annotations, no output schema, and 0% schema description coverage for two parameters. The description covers side effects, undo behavior, and the critical index-shifting edge case, which is good. However, it omits when to prefer this tool over siblings like delete_clip or move_arrangement_clip, and does not fully compensate for the lack of parameter descriptions on track_index. It is adequate for a simple two-parameter deletion but not complete.

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 both parameters. It explains clip_index's semantic scope ('indexes Track.arrangement_clips') and gives a concrete example with two integers, but track_index is only indirectly clarified through the example. It adds useful meaning for one parameter and partial context for the other, which is adequate but leaves room for more explicit parameter documentation.

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 opens with a specific verb and resource: 'Delete one clip from the Arrangement timeline.' It clearly distinguishes Arrangement clips from Session clips, which matters because the sibling list contains delete_clip, fire_clip, and multiple arrangement-specific tools (get_arrangement_clips, move_arrangement_clip, set_arrangement_clip_properties). An agent can identify the exact operation without ambiguity.

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 this tool versus delete_clip, move_arrangement_clip, or clear_clip_notes. The example and edge-case note imply usage but do not state conditions or alternatives. The description says what it does but not when the agent should choose it over similar deletion or arrangement tools.

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?

With no annotations, the description carries the full burden and does well by disclosing the destructive side effect ('deletes a clip in one Live undo step') and an edge case ('empty slots return BAD_INPUT'). It doesn't cover whether permissions are needed or whether associated data is removed, but the core behavioral traits are present.

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 three compact sentences, front-loading the core action and then adding side effects and edge cases. No wasted words, though the example sentence could be slightly more informative.

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 delete tool with no annotations and no output schema, the description covers the action, side effects, and an error condition. However, it leaves a significant gap in parameter semantics and does not explain return values or any prerequisites, so it is adequate but not complete.

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. It provides only an example ('delete_clip(0, 1) removes the clip in slot one') without explaining what track_index and clip_index mean, whether indexing is 0-based or 1-based, or how the parameters relate to Ableton's track/slot model.

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 ('Delete') and resource ('Session clip slot'), making it clear that this operates on session clips rather than arrangement clips. However, it does not explicitly name the sibling 'delete_arrangement_clip' to sharpen 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?

Usage is implied by the operation itself, and the edge case note about empty slots returning BAD_INPUT gives a constraint. But there is no explicit guidance on when to choose this tool over alternatives like clear_clip_notes or delete_arrangement_clip.

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?

With no annotations present, the description carries the full behavioral burden and does so well: it discloses the mutation ('mutates the Set in one undo step'), the side effect on the playhead ('temporarily moves the playhead'), the no-op return case ('deleted: false'), and a named failure mode ('raises CUE_SNAPPED_TO_GRID'). This is exactly the kind of side-effect and error disclosure an agent needs before invoking a destructive operation.

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 action and mechanism, then ordered side effects, example, and edge cases in a compact block with no filler sentences. 'Verified move-and-toggle' is mildly jargon-y but is immediately grounded by the concrete example.

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 mutation with no output schema and no annotations, the description covers side effects, failure modes, and the negative return case, which is nearly complete. It stops short of describing the successful return payload or idempotency/retry behavior after a CUE_SNAPPED_TO_GRID failure.

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 0% (the lone 'time' number parameter has no description), so the description must compensate. The example 'delete_cue_point(8.0) deletes a cue near beat eight' establishes that time is expressed in musical beats rather than seconds and that matching is approximate — meaningful information absent from the schema, though the tolerance/precision itself is left unspecified.

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 and resource ('Delete a cue point') with an unambiguous target, and no sibling in the list performs this operation (create_cue_point and bulk_create_cue_points are additive). The added mechanism note ('verified move-and-toggle') further pins down what the operation actually does at the DAW level.

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 gives a concrete invocation example and edge-case behavior, which implies usage, but never states when to prefer this tool over related deletion tools such as delete_arrangement_clip, nor any prerequisites or when-not conditions. Usage is inferable but not explicit.

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 are absent, so the description must carry the behavioral load. It explicitly states 'Side effects: none', gives a concrete example of the return shape (automatable parameters or setup_requests), and describes edge cases including has_instrument: false. It does not cover permissions, rate limits, or determinism, keeping 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?

Front-loaded with the core action, then side effects, example, and edge cases in a compact, well-organized structure. No sentence is wasted.

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 one-parameter inspection tool with no output schema, the description covers purpose, side effects, example output, and edge cases. The main missing piece is guidance on where track_index comes from and how this relates to sibling inspection 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?

Schema description coverage is 0% and the single parameter track_index is undocumented in the schema. The description's example uses track_index=60 but never explains the index's origin, range, or relation to other track-identifying tools, leaving a real 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 states a clear verb ('describe') and resource (a track's instrument) and adds the distinguishing scope of what the user must still set up. It is not a tautology. It does not explicitly name siblings like get_track_state or get_device_list to differentiate, 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?

The example and edge-case notes imply when the tool is useful (checking whether an instrument exists or needs setup), but there is no explicit when-to-use or when-not-to-use guidance and no named alternatives for similar queries such as get_track_state.

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?

With no annotations, the description carries the full load and does so: it declares 'Side effects: none; a read-only sweep', and discloses the edge-case behavior (returns arrangement_supported:false plus an inaccessible entry rather than reporting zero clips). This is exactly the behavioral context an agent needs before trusting the output.

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 purpose, then side effects, examples, and edge cases in a compact block. Every sentence earns its place, though the edge-case sentence is dense enough to slow a quick scan.

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-param read-only diagnostic with no output schema, the description covers purpose, safety, both call forms, and a non-obvious return edge case. Nothing an agent needs to invoke or interpret the tool correctly 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 0%, so the description must compensate, and it does: it explains that a supplied index inspects one track while the no-argument form sweeps the whole Set. That fully specifies the meaning and default behavior of the single optional parameter.

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 (report) and resource (clips reachable by set_clip_color), and ties itself to the sibling tool it supports. An agent can tell it apart from get_clip_info or get_arrangement_clips: this is a diagnostic reachability check, not a data fetch.

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 two examples give clear context for when to pass a track index versus sweep the whole Set, which effectively distinguishes a per-track check from a full-set audit. It doesn't explicitly say 'run this before set_clip_color', but the framing makes the intended workflow evident.

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?

With no annotations provided, the description carries the full burden and does well by stating 'Side effects: none' and documenting edge cases like audio clips returning WRONG_TYPE and omitting scale skipping pitch analysis. It still does not describe the returned diagnostic structure, but the key safety and behavior context is present.

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 compact, front-loaded with the core action, and uses labeled lines for side effects, example, and edge cases. Every sentence adds useful information without 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?

For a tool with no annotations, no output schema, and 0% schema coverage, the description covers purpose and some edge cases but leaves return values and detailed parameter meaning undocumented. It is adequate but incomplete given the weak structured metadata.

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. It partially does so through the example call and the note that omitting scale skips pitch analysis, but it does not explain what track_index and clip_index represent or what values scale_root and scale_type accept beyond the example.

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 uses a specific verb, 'Scan', names the exact resource, 'MIDI clip', and enumerates the diagnostics: overlapping notes, notes outside scale, and quantization issues. It also distinguishes itself from audio analysis by noting that audio clips return WRONG_TYPE.

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 example and edge cases imply when the tool is useful, but the description does not explicitly compare it to alternatives such as get_clip_notes, diagnose_clip_targets, or analyze_audio. Usage is inferable but not directly guided.

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?

With no annotations, the description carries the full burden and does disclose key behavior: "Side effects: none; no socket call is made" and the edge case that lists are compared by position, not identity. These are genuinely useful traits not derivable from the schema. Return-format detail is thin, though the output schema covers that.

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 action, then labeled subsections (side effects, example, edge cases). It is efficient, though the fragmented "Example:/Edge cases:" labeling is slightly choppier than a flowing sentence would be.

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 values need not be described, and the description still adds the changed-paths behavior. Combined with the explicit side-effect and comparison-semantics notes, this is nearly complete; only the upstream relationship to take_snapshot is 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 0%, so the description must compensate. The example ``diff_snapshots_tool(old, new)`` hints at ordering (old vs new) and the params are clearly two snapshots, but the description does not define what a "snapshot" object should contain or how the two args differ. It partially compensates but leaves the parameter meaning under-specified.

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 and resource ("Compare two snapshots") plus the scope qualifier "on the MCP-server side," and the example clarifies it "reports changed paths." It does not explicitly distinguish itself from the related take_snapshot sibling, so it falls short of the top mark.

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 agent can infer this runs over snapshots (presumably from take_snapshot), but no when-to-use, prerequisites, or named alternatives are given. The example supplies a calling pattern rather than guidance on when this tool is the right 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?

With no annotations provided, the description carries the full burden and does so well: it discloses that it adds exactly one Arrangement clip in one undo step, that the Session clip is unchanged, that envelopes travel with the copy, and it names two error codes (BAD_INPUT for empty slot, CAPABILITY_UNAVAILABLE for unsupported hosts). It stops short of stating the successful return value or any permission requirements.

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-loads the purpose, then cleanly sections side effects, an example, and edge cases. Every sentence carries information (undo semantics, envelope behavior, error codes) with 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?

For a mutation tool with no annotations and no output schema, the description covers purpose, side effects, a concrete example, and failure modes. The only meaningful gap is the success return value, which the absence of an output schema leaves slightly open.

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. The worked example maps each positional argument to a meaning — 38 = track, 0 = slot one (zero-based), 468.0 = beat — and 'at an exact beat' clarifies the time unit. This effectively documents all three parameters, though it does so by example rather than explicit per-parameter prose.

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: placing a Session clip onto the Arrangement timeline at an exact beat. This clearly distinguishes it from siblings like move_arrangement_clip, delete_arrangement_clip, and get_arrangement_clips, which operate on existing Arrangement clips rather than duplicating from a Session slot.

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 example and edge cases imply intended usage, but there is no explicit guidance on when to use this versus alternatives (e.g., fire_clip, create_clip, or move_arrangement_clip). Usage is demonstrated rather than framed, so it is adequate but leaves 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?

With no annotations, the description carries the full burden and does so reasonably: it discloses the side effect ('reads the file from disk'), states what is returned (detected pitch plus single-cycle sample buffer), and describes edge-case behavior (aperiodic content returns {ok: False, reason: ...} instead of crashing). It stops short of covering invalid paths or permission failures.

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 purpose is front-loaded, then side effects, example, and edge cases follow as labeled fragments. Every line carries signal and there is no filler, though the formatting is a bit terse and line-broken.

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 2-param tool with no annotations or output schema, the description supplies return content and error behavior, which is helpful. However, the undocumented frame_size parameter and absence of any when-to-use guidance leave gaps an agent must guess around.

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 only demonstrates 'path' through the example. The 'frame_size' parameter (default 2048) is never mentioned in the description, so an agent has no added meaning for what it controls or how it affects detection.

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 ('Find') and resource ('a candidate single-cycle loop in a local audio file plus its detected pitch'), so an agent knows exactly what comes out. It implicitly separates itself from session-state siblings by specifying 'a local audio file', but it never explicitly names a sibling alternative like analyze_audio.

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 concrete example (extract_single_cycle(path="/stems/kick.wav")) and the 'local audio file' framing imply the intended context, but there is no explicit when-to-use vs. when-not guidance and no reference to related tools like analyze_audio or the groove family.

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?

With no annotations, the description carries the full burden and does reasonably well: it discloses side effects (reads both files), an error path (mismatched sample rates raise a structured error), and a guard (identical paths are rejected). It stops short of describing the return payload or any performance/rate concerns.

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 core comparison is front-loaded, followed by succinct side-effect, example, and edge-case lines. Every line adds information, though the 'Side effects: reads both files' line is thin relative to its dedicated slot.

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, annotation-free tool with no output schema, the description covers inputs and error behavior but only vaguely gestures at the return ('suggests band-level cuts') without saying what data comes back. That leaves an agent unable to anticipate the response shape.

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, and it does: it explains that target_path is compared against reference_path and that threshold_db is the dB margin (default 6 in schema) above which a band qualifies. The path parameters' expected content (e.g., file vs track identifiers) is still left implicit.

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 operation: identify frequency bands where target_path exceeds reference_path by threshold_db dB. The verb ('Identify') and resource ('frequency bands') are concrete and computable. It doesn't explicitly contrast with near-neighbour analysis tools like analyze_mix or analyze_audio, 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?

The worked example shows a concrete invocation, and edge cases note the failure modes, which implies when it applies. However there is no explicit when-to-use or when-not-to-use guidance versus alternatives, and no stated prerequisites beyond implied file paths.

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?

With no annotations, the description carries the full burden and does well: it discloses the side effect ('launches playback in one undo-scoped command') and failure behavior ('empty or invalid slots are rejected'). It omits launch quantization/queuing semantics, but the safety-relevant behavior is covered.

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?

Four short labeled lines (purpose, side effect, example, edge cases) with the primary action front-loaded. Every sentence contributes something the agent cannot get from the 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?

No output schema exists, so return values need not be explained, and the description supplies purpose, side effect, example and failure modes for a simple two-parameter mutation. Adequate for this complexity level, with room only for launch-timing detail.

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 both params are bare integers, but the example 'fire_clip(0, 1) launches slot one on track zero' disambiguates argument order (track_index first, clip_index second) plus the numbering, which is the key ambiguity an agent would otherwise face.

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: 'Fire an existing Session clip through its clip slot.' This is enough to tell it apart from get_clip_info and fire_scene (a clip vs a scene), though it never names the nearest sibling 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?

'Fire an existing Session clip' implies the launch use case and the precondition that the clip must exist, but there is no explicit when/when-not guidance or mention of alternatives such as fire_scene or start_playback. Usage is inferable rather than 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?

With no annotations, the description carries the full burden and largely succeeds: it discloses the side effect (triggers all playable clips in the selected scene), the timing behavior (uses current launch quantization), and the error case (out-of-range index returns INVALID_PARAMS). It omits reversibility and what happens on partially-empty scenes, keeping it short of 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?

Three tight sentences, each earning its place: purpose first, then side effects, then example and edge case. Front-loaded and scannable with 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?

For a single-parameter action tool with no annotations and no output schema, the description covers purpose, side effects, an example, and the failure mode. Near-complete; only the acceptable index range is 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 0%, so the description must compensate. The example 'fire_scene(0) launches the first scene' does establish that the index is zero-based, which the bare integer schema does not convey, but range bounds and valid max are not given beyond the generic INVALID_PARAMS note.

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 (fire) plus resource (Session scene) and adds the launch-quantization qualifier, so the agent knows exactly what action occurs. It does not explicitly name the closely-related sibling fire_clip, but the resource distinction makes them separable.

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 context is implied ('one Session scene') and reinforced by a concrete example, but there is no explicit when-to-use / when-not guidance and no reference to alternatives such as fire_clip or get_scenes for discovering valid indices.

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?

With no annotations, the description carries the load and does well: it discloses the side effect (local file read, no Live contact) and the edge case (diagnostic string when no log is found). It omits permission requirements and any bound on read size beyond the example.

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 purpose, then side effects, a concrete example, and edge cases. Four short lines with zero filler; every sentence adds usable information.

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-optional-param, read-only diagnostic tool with an output schema already covering the return shape, the description supplies purpose, side effects, usage example, and failure behavior. Nothing needed to invoke it correctly 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 0% and the lone 'lines' parameter is undocumented in the schema, but the example get_ableton_logs(50) -> last fifty lines clearly conveys the parameter's meaning and unit. The default of 100 is only in 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 verb and resource (read the tail of the newest Ableton Log.txt) with a Windows platform scope. It also distinguishes itself from every sibling by clarifying it operates on a local file rather than the Live session.

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 'does not contact Live' note implies diagnostics use, but no explicit when-to-use condition or named alternative is given. An agent must infer that this is the fallback when the bridge/session tools fail.

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?

With no annotations, the description carries the full burden and does well: it declares 'Side effects: none', specifies the return fields (start_time, end_time, length in beats, sorted by position), and documents the CAPABILITY_UNAVAILABLE edge case rather than an empty list. It does not state permissions or pagination behavior, but for a local read tool the disclosure is above average.

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-loads the one-line purpose, then cleanly separates Side effects, Example, and Edge cases. Every sentence earns its place, though the sectioned formatting is slightly more verbose than a single tight paragraph would be.

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 one-param read tool with no output schema, the description covers return shape, ordering, side effects, and a failure mode, which is close to complete. The remaining gap is how to obtain a valid track_index and the indexing convention.

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 single required track_index. The example get_arrangement_clips(3) demonstrates that the argument is an integer track index, but it never explains what the index refers to (0- vs 1-based) or that it comes from get_track_list, leaving a real 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?

States a specific verb ('List'), resource ('Arrangement clips'), scope ('one track's'), and the aspect returned ('their placement on the timeline'). The phrase 'Arrangement clips' distinguishes it from the many session-clip siblings (get_clip_summary, get_clip_info, get_clip_notes), so an agent can route correctly without opening the 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?

Usage is only implied by the tool's purpose; there is no explicit 'use this when…' or a named alternative such as get_clip_info for session clips. The agent can infer it is for inspecting a track's arrangement timeline, but no when-not or prerequisite guidance is given.

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?

With no annotations, the description carries the full burden and does so well: it discloses side effects ('opens a loopback connection and performs one read-only session query'), implying a safe read operation, and flags an edge case (WSL NAT failures with a Windows-Python launcher hint). It omits anything about latency or failure semantics beyond the edge case.

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 purpose followed by labeled 'Side effects', 'Example', and 'Edge cases' lines — every sentence earns its place with no padding. The labeled structure is compact and scannable.

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 detail is unnecessary. For a zero-parameter diagnostic probe, purpose, side effects, and one edge case are sufficient to invoke it correctly; only alternative-routing guidance 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?

Zero parameters, so the schema-side burden is nil and the baseline is 4. The example call 'get_bridge_status()' confirms the no-argument invocation.

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 and resource — 'Probe the Live bridge' — and frames the goal as explaining connection failures, which is distinct from the session-data siblings like get_session_overview. It doesn't explicitly name a sibling, but the diagnostic intent is unambiguous.

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?

Implies usage ('explain environment-specific connection failures', 'distinguishes MCP discovery from Live availability') but never states when to reach for it versus alternatives, nor any explicit when-not condition. Adequate but leaves the trigger context 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?

No annotations are provided, so the description carries the full behavioral burden. It states 'Side effects: none' and documents edge cases (version-specific missing categories omitted), which is useful transparency for a read-only listing tool, though it does not discuss connection requirements or pagination.

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 cover purpose, side effects, return example, and edge cases with no filler. The purpose is front-loaded.

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 the tool's simplicity, no output schema, and no annotations, the description supplies enough context to call it correctly: it explains the return type and edge cases. The only missing piece is when-to-use guidance versus siblings, which is already penalized in usage_guidelines.

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 input parameters, so the schema has no parameter semantics to convey. The description's example `get_browser_categories()` confirms the no-argument call, which is a minor addition beyond the empty 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 verb ('List') and resource ('top-level Live Browser categories') and scopes it to the current version. It does not explicitly name alternatives such as search_browser or get_device_list, but the resource distinction is clear.

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?

No when-to-use guidance or alternatives are provided. The example shows how to call it, but it does not explain when an agent should choose this over search_browser or other browser-related tools.

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?

With no annotations the description carries the full burden, and it does so well: it declares 'Side effects: none,' discloses that results are sampled at 'resolution' beats because the LOM exposes no breakpoint list, and warns that a duplicate parameter name yields AMBIGUOUS_MATCH unless device_index is supplied. Return shape is described only loosely ('sampled curve'), which is the main remaining gap.

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 core purpose is front-loaded in the first sentence, followed by labeled 'Side effects' and 'Edge cases' blocks and a compact example. Most sentences earn their place; the 'intent compared against reality' clause is slightly rhetorical but still useful framing.

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 5-parameter read tool with no annotations and no output schema, the description covers side effects, sampling semantics, disambiguation, and an invocation example. It is complete enough to call correctly; only an explicit return-format description is missing, which is acceptable given the sampled-curve framing.

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 0%, so the description must compensate, and it largely does: it clarifies resolution (sample spacing in beats), device_index (disambiguation under AMBIGUOUS_MATCH), and parameter_name (may be shared across devices). The positional example (38, 0, 'FILTER', resolution=0.5) implicitly documents track_index and clip_index order.

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: 'Read back one clip envelope as a sampled curve.' The read framing cleanly distinguishes it from siblings that write automation (create_clip_automation, create_clip_automation_curve) and from clip-metadata readers like get_clip_info or get_clip_notes.

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 gestures at usage via 'returns the written shape so intent can be compared against reality,' which implies a verification use case, but it never states when to prefer this over get_parameter_value, get_clip_info, or the read counterpart of the automation tools. Usage is implied rather than explicit, and there are no exclusions.

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?

With no annotations, the description carries the full burden and does well: it explicitly declares "Side effects: none", lists the returned fields (loop, type, color, signature), and discloses the empty-slot behavior of returning has_clip=false rather than erroring. It omits permission requirements and the shape/exact types of the return object, but the core behavioral profile is clear.

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?

Four tight lines, front-loaded with the purpose, then labeled Side effects / Example / Edge cases. Every sentence earns its place 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?

There is no output schema or annotation, so the description is the sole source of truth and does cover the safety profile, sample return fields, and the empty-slot edge case. It would be stronger if it named the index semantics and a representative return structure, but it is sufficient to call 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 coverage is 0% — neither parameter has a description — so the description must compensate. The example `get_clip_info(0, 1)` implies positional order but never states which argument is track_index vs clip_index, nor what valid ranges or addressing scheme apply. This leaves a real gap for a two-parameter lookup.

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 and resource ("Read stable metadata for one Session clip slot") and the word "stable" hints at a distinction from mutable/derived views. However, it does not name sibling alternatives like get_clip_summary, get_clip_notes, or get_clip_automation, so the agent must infer which clip reader to pick.

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 agent gathers that this is the tool for slot-level metadata. There is no explicit when-to-use/when-not guidance against the many sibling clip tools, though the edge-case note (empty slots return has_clip=false) usefully tells the agent this call is safe to probe blind.

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?

With no annotations, the description carries the burden and does well: it states 'Side effects: none,' documents an example invocation, and specifies concrete edge-case behavior (WRONG_TYPE for audio clips, empty list for empty slots). It doesn't state auth/permission needs or whether the operation requires the clip to be loaded/armed, but covers the key failure modes.

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 compact lines: purpose, side effects, example, edge cases. No filler, front-loaded with the core purpose, and structured for fast scanning.

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 reasonably fills the gap by naming return behavior (MIDI notes, empty list, WRONG_TYPE). It could specify return shape (note fields: pitch, velocity, timing) to fully substitute for a missing output schema, but overall it is adequately complete for a simple two-param read 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 coverage is 0% with no param descriptions, so the description must compensate. The example 'get_clip_notes(0, 1) reads slot one on track zero' clarifies that the first arg is track_index and the second is clip_index, which is useful. It doesn't explain index origin (0-based confirmed by example) or valid ranges, and relies on a single example.

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+scope: 'Read MIDI notes from one Session clip.' It distinguishes itself from siblings like get_clip_info, get_clip_summary, and get_clip_automation by naming the exact return (MIDI notes) and the exact container (one Session clip).

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 implies the usage context (reading notes from a single clip) but doesn't state when to prefer this over get_clip_info, get_clip_summary, or diagnose_midi_clip. No explicit when/when-not 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?

With no annotations provided, the description carries the full behavioral burden and does disclose the key traits: 'Side effects: none' establishes it as a safe read, and the edge case documents the WRONG_TYPE failure for return/master tracks. It stops short of describing return format or ordering, which would complete the picture.

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 in the first line, followed by a labeled side-effects note, a concrete example, and an edge-case warning. Every sentence is short and load-bearing, with no redundant restatement of the tool name.

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 is the only source of information. It covers purpose, safety, example, and one error case, but says nothing about what the returned slot/clip metadata contains or its ordering, leaving an agent guessing about the response shape for a listing 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 coverage is 0% and the lone parameter (track_index) has no schema description, so the description must compensate. The example 'get_clip_summary(0)' combined with 'lists the first track's slots' communicates that the argument is a zero-based track index, which is real semantic value beyond the bare integer type.

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 (List) plus the resources (Session clip slots and clip metadata) and scope ('for one track'), so an agent can tell it enumerates clips on a track rather than returning a single clip. It does not explicitly differentiate itself from siblings like get_clip_info, get_clip_notes, or get_track_list, which keeps it just 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?

The example ('get_clip_summary(0) lists the first track's slots') implies intended usage and the edge case ('return and master tracks produce WRONG_TYPE') gives a partial when-not-to-use constraint. However, no sibling alternative is named for retrieving clip details versus a slot listing, so guidance is implied rather than explicit.

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?

With no annotations, the description carries the full burden. It does disclose 'Side effects: none' (read-only) and warns that large Sets produce large JSON results, which is useful behavioral context, but it says nothing about output structure or size thresholds beyond the vague warning.

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 purpose in the first sentence, followed by compact side-effect, example, and edge-case notes. Reasonably tight, though the example line restates the summary somewhat.

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 no-arg read tool with no output schema, the description adequately signals what comes back (tracks, scenes, unnamed tracks) and that results scale with Set size. It falls short on differentiating from the several read siblings that return overlapping data.

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 there is nothing for the description to clarify. Baseline 4 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?

Clear verb 'Retrieve' with a specific resource: 'full track layout, scene count, and composition properties'. However, it does not distinguish itself from overlapping siblings like get_track_list, get_scenes, get_session_overview, and get_project_metadata, leaving the agent to guess which one to pick.

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?

No when-to-use or when-not-to-use guidance is provided. Given the heavy overlap with get_track_list, get_scenes, and get_session_overview, the absence of any routing condition is a notable 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?

With no annotations, the description carries the burden and explicitly states 'Side effects: none' plus the edge case that unavailable surfaces may be omitted. That is meaningful behavioral disclosure for a read-only list 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?

Three compact sentences front-loaded with purpose, then side effects, example, and edge case. 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?

For a zero-parameter, read-only discovery tool with no output schema, the description covers purpose, safety, example, and a relevant caveat. It does not describe the return shape, but that is the only notable 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?

Zero parameters, so baseline is 4. The description correctly implies no arguments via the empty call example, and no parameter semantics are needed.

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 and resource: list MIDI Remote Scripts exposed by Live. It is clearly distinguishable from session/device/track siblings because no other tool references control surfaces.

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?

Gives a concrete example use case ('confirms this script loaded') and notes that unavailable surfaces may be omitted, but provides no when-to-use vs alternatives or exclusions. Adequate but limited for a discovery tool.

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?

With no annotations, the description carries the full burden and does disclose useful behavior: 'Side effects: none' (read-only) and an edge case (a non-rack device returns WRONG_TYPE). It does not describe pagination or the exact return shape, but the safety and failure profile are covered.

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 purpose, then side effects, example, and edge cases in clearly labeled fragments. Every sentence adds value and nothing is wasted.

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 moderate read tool with no output schema and no annotations, the description covers purpose, read-only nature, error behavior, and a concrete example. The main gap is that the two undocumented parameters are only weakly explained via the example.

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 two parameters are undocumented in the schema, so the description must compensate. The example get_device_chains(39, 0) only implies argument order/roles (track_index, device_index) without explaining them, so compensation is 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 ('list its chains, their mixer state and inner devices') and scopes it to 'one rack.' It explicitly contrasts with the sibling get_device_list, noting what that tool 'cannot show,' so an agent can distinguish them 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?

It names the alternative (get_device_list) and the reason to prefer this tool (chain-level and mixer-volume detail), plus a concrete example. It lacks explicit when-not-to-use conditions or prerequisites, but the routing context is clear.

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?

With no annotations present the description carries the full burden, and it does disclose key traits: explicit "Side effects: none," the return format ("returns device path-ids"), and a meaningful edge case about special tracks returning empty lists. It stops short of permissions or pagination, but for a simple read tool this is solid disclosure.

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?

Four short, labeled lines that are front-loaded with the purpose and each add distinct information (side effects, example, edge cases). No filler or repetition.

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 one-parameter read tool with no output schema or annotations, the description supplies the purpose, safety profile, sample return shape, and an edge case. The only gap is that the sole parameter's meaning is left partially 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 description coverage is 0% and the single parameter track_index is undocumented in the schema. The example "get_device_list(0)" implicitly conveys that it is a zero-based track index, but no explicit semantics, valid range, or relationship to other track identifiers is given.

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 clear verb and resource ("List devices and parameter snapshots") scoped to a single track. An agent can identify the operation, though the phrase "parameter snapshots" slightly blurs the line with the sibling list_device_params, and no sibling is named to disambiguate.

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 "on one track" hints at scope, but there is no explicit when-to-use guidance, no prerequisites, and no routing to alternatives such as list_device_params, get_device_chains, or get_track_list. The agent must infer selection from the name alone.

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?

With no annotations, the description carries the full burden and does well: 'Side effects: none' establishes the read-only profile, the example shows the return shape, and the edge case about Live beat-time objects serializing as floats is a genuinely useful implementation detail. It does not cover pagination or whether very large cue lists are truncated, but for a zero-argument read tool this is solid disclosure.

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 labeled segments (purpose, side effects, example, edge case) that are front-loaded and waste-free; each sentence adds information an agent would otherwise have to guess.

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 contract, and it does so with a concrete example object and the float-serialization caveat. Combined with the clean side-effect statement, nothing needed to call and interpret this tool 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 takes no parameters, so the baseline is 4; there is nothing for the description to clarify or compensate for on this dimension.

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 ('List') and resource ('Arrangement cue points') plus the payload ('names and beat times'), which cleanly separates it from the mutating cue-point siblings (create_cue_point, bulk_create_cue_points, delete_cue_point). An agent can identify it without opening any 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?

Usage is implied by 'List Arrangement cue points' and the read-only framing, but the description never says when to reach for this versus get_arrangement_clips, get_composition_structure, or the cue-point creation tools. No explicit alternatives or exclusions are given.

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?

With no annotations, the description carries the full burden, and it does disclose 'Side effects: none' plus the useful edge case that values can change with user interaction during a session. It adds nothing about permissions, caching, or refresh/polling behavior, so it is only partially complete for an annotation-free 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?

Front-loaded with the purpose and organized under clear labels (Side effects, Example, Edge cases). The Example line is nearly redundant for a zero-argument call, a small amount of padding against an otherwise tight structure.

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, zero-parameter tool with no output schema and no annotations, the description usefully states the return content ('loop geometry in beats'), the safety profile ('Side effects: none'), and a behavioral caveat. It is complete enough to call correctly, missing only the read-only confirmation an annotation would normally supply.

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 there is nothing to disambiguate and the baseline is 4. The description does not introduce parameter concepts that could mislead.

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 ('Read') and precise resource ('Arrangement loop enablement, start, and length'), so the agent knows exactly what is returned. It implicitly contrasts with the write siblings (set_loop, set_loop_start, set_loop_length) but never names the distinction, so it falls short of the 5 bar for explicit sibling 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?

There is no guidance on when to use this versus the many read siblings (get_scenes, get_track_state, get_locators) or versus the set_loop* writers. The example just restates a parameterless call rather than explaining a scenario that selects this tool.

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?

With no annotations, the description carries the full burden and does disclose the key traits: 'Side effects: none' (safe read), the edge-case return value rewrites_input: false for tracks without such a device, and a worked example of what the report surfaces. It omits connection/permission requirements and any timing or rate considerations.

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 purpose sentence followed by labeled Side effects, Example, and Edge cases lines. Every sentence carries distinct information 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?

No output schema exists, so the description does its part by naming the rewrites_input field and explaining the Note Length scenario. Rewriting the response shape and the index convention would make it fully self-sufficient for a one-parameter read 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% for the single required track_index integer, so the description must compensate. The example get_midi_chain_report(58) confirms an integer index is expected, but it never clarifies whether the index is zero-based or what ordering it indexes into, leaving a real gap for a required parameter.

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 verb (report) and a narrowly defined resource: MIDI effects that rewrite clip input. The phrase 'rewrite what a clip says' plus the Note Length example makes the scope concrete enough to separate it from generic siblings like get_device_chains or list_device_params, though it does not name those alternatives directly.

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?

Gives a clear timing cue ('before writing one'), which implies it should be consulted prior to add_notes_to_clip or clip creation so written durations aren't silently overridden. It stops short of naming an explicit alternative tool or a when-not-to-use condition.

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?

With no annotations, the description carries the full burden. It discloses 'Side effects: none', describes the return of bounds, and explains an edge case where missing parameters return INVALID_PARAMS. It doesn't discuss authentication or performance, but for a read operation the disclosed behavior is substantial.

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 front-loaded with purpose and side effects, followed by concise examples and edge cases. It is slightly long due to the examples, but each section earns its place by disambiguating complex nested parameters.

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 5-parameter tool with no output schema and no annotations, the description covers purpose, side effects, parameter usage, and critical edge cases. It is nearly complete, though it could mention the return format or whether bounds are always returned.

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. It provides concrete examples showing how track_index, device_index, chain_index, chain_device_index, and parameter_name are used, including the behavioral nuance that chain_index alone addresses a chain mixer with limited parameters. This adds significant meaning beyond 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 states a specific verb and resource ('Read a named device parameter and its bounds'), which clearly distinguishes it from the sibling set_parameter_value and other get_* tools. The purpose is unambiguous and scoped to exactly one operation.

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 examples show how to call the tool for top-level and nested parameters, which implies when to use it, but there is no explicit guidance on when to use this tool versus list_device_params or get_selected_context. The context is clear enough to infer, but alternatives are not 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?

With no annotations, the description carries the full burden and largely meets it: 'Side effects: none' declares the read-only nature, and the error codes (WRONG_TYPE, PLUGIN_NOT_CONFIGURED) disclose failure behavior beyond the schema. It omits prerequisites such as the Live bridge needing to be running and any notes on result size for plugins with many presets.

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 purpose sentence, then labeled Side effects / Example / Edge cases sections, each earning its place with distinct information. No filler or restatement of the name.

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?

Without an output schema or annotations, the description steps in by naming return fields (preset names plus selected_preset_index) and enumerating error states. The remaining gap is index resolution — which base the indices use and how to discover device_index for a track.

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 0% and both parameters (track_index, device_index) are undescribed in the schema, so the description must compensate. The example get_plugin_presets(2, 2) implies the first argument is the track, but the indexing base (0- vs 1-based) is ambiguous, the device_index semantics are never explained, and there is no pointer to how to obtain a valid device index.

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 and resource ('List a VST/VST3/AU plugin's presets') plus an extra output facet ('report its Configure state'), which clearly separates it from set_plugin_preset and list_device_params. It does not explicitly name a sibling to contrast with, but an agent can still route correctly.

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 edge-case section gives an effective when-not condition: native Live devices return WRONG_TYPE and unconfigured plugins report PLUGIN_NOT_CONFIGURED, so the agent knows which inputs won't work. It stops short of naming an alternative to use instead (e.g. set_plugin_preset or browser search) for those cases.

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?

No annotations are provided, so the description carries the behavioral burden, and it does disclose 'Side effects: none,' making the read-only nature explicit. It also surfaces a non-obvious edge case (unsaved Sets have an empty file path), which is genuinely useful behavioral context, though it says nothing about error or return semantics.

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 front-loaded with the payload before side effects, examples, and edge cases, and every sentence adds some value. The example line ('get_project_metadata() identifies the loaded Set') is mildly redundant with the opening sentence and could be trimmed.

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 cover returns, and it does by enumerating the three fields (name, path, dirty state) plus the unsaved-Set edge case. It would be stronger if it distinguished the returned data from the overlapping get_session_* siblings, but for a zero-param read it is otherwise complete.

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 the baseline is 4 and there is no parameter behavior the description could clarify. The schema's empty object is self-explanatory and the description correctly implies a callable-with-no-args operation.

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 ('Read') and the exact fields returned (Set name, file path, dirty state), so the resource and payload are unambiguous. It does not, however, differentiate itself from overlapping siblings like get_session_overview or get_session_info, which likely also expose project/session identity data.

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 usage signal is the example 'get_project_metadata() identifies the loaded Set,' which implies a scenario but gives no explicit when-to-use, when-not, or alternatives. With several sibling introspection tools (get_session_info, get_session_overview, get_selected_context) available, the absence of routing guidance is a real 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?

With no annotations, the description carries the full burden and does so well: it explicitly declares 'Side effects: none' and documents a real edge case (unavailable routes returned as empty strings). It stops short of describing return structure beyond the label concept, but the key behavioral traits are disclosed.

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?

Four short lines, each earning its place: purpose first, then side effects, a concrete example, and edge-case behavior. Front-loaded and waste-free.

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 supplies an example and edge-case behavior, which is sufficient to call it correctly. The main residual gap is the absence of any detail on the shape of the returned routing labels.

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 integer track_index is undocumented in the schema. The example 'get_routing(0) reports the first track's routes' implies a 0-based track index, adding meaningful interpretation, but does not define valid range or behavior for out-of-range indices.

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 and resource ('Read input and output routing labels') with a clear scope ('for one track'). No sibling tool handles routing, so it is naturally distinguishable, though it never explicitly contrasts itself with the many other get_* readers such as get_track_state or get_track_list.

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 the purpose and the example call, and the 'for one track' scope clarifies the granularity, but there is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives to consult instead.

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?

With no annotations available, the description carries the full burden and does well: 'Side effects: none' explicitly declares the read-only profile, and the edge-case sentence defines exactly what non-empty means ('any contained slot has a clip'). It stops short of stating ordering, count, or whether empty scenes are still returned, which would round out the behavior.

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?

Four short, labeled sentences: purpose first, then side effects, then an example, then edge cases. Nothing is redundant and the most important information is front-loaded.

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 reasonably steps in by describing the return content (scene indexes and names) and the emptiness semantics. It is nearly complete for a zero-argument read tool, missing only ordering and how many scenes are returned.

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 schema is trivially empty and the description correctly does not invent parameter semantics; there is nothing further needed here.

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 and resource ('List Session View scenes') plus the extra output dimension (emptiness), so an agent knows exactly what it returns. It does not, however, differentiate itself from the close sibling get_scene_state, leaving the boundary between 'list all scenes' and 'scene detail' to inference.

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 or when-not-to-use guidance, and the very relevant sibling get_scene_state is never mentioned as the alternative for per-scene detail. Usage is only implicit from the tool name, which the description neither reinforces nor qualifies.

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?

No annotations provided, so the description carries full burden. It correctly states 'Side effects: none' (a read operation) and the error behavior ('invalid scene index returns INVALID_PARAMS'). This covers the key behavioral facts an agent needs. Missing detail on rate limits or return format, but strong for a read-only 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?

Four short, front-loaded lines with no waste. The example and edge case are useful, not filler. Slightly fragmented structure (labeled lines) but each earns its place.

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-param read tool with no output schema, the description covers purpose, side effects, an example, and error behavior. The main miss is not clarifying indexing semantics or the parameter explicitly, and not distinguishing from get_scenes.

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 0% and the single parameter (scene_index) is undocumented in the schema. The description helps indirectly: the example 'get_scene_state(0) inspects the first scene' implies 0-based indexing, and the edge case mentions invalid indices. However, it never states the parameter name, type, or that it's required. Partial compensation but a clear 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?

Clear specific verb+resource: 'Read one scene and its per-track clip-slot summary.' An agent understands exactly what it gets. Doesn't explicitly differentiate from siblings like get_scenes (plural) or get_clip_summary, but the singular-scene scope is reasonably inferable.

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?

No when-to-use guidance or alternatives named. The example shows a call but not when to prefer this over get_scenes. An agent must infer the distinction. This is a significant gap given the large sibling set containing get_scenes.

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?

No annotations are provided, so the description carries the full burden, and it does add real behavioral context: 'Side effects: none' declares the safety profile, and the edge-case note (absent selections return null or index -1) is exactly the kind of return-value behavior an agent needs. It doesn't describe output shape, but the empty input schema and no-param nature limit what else is required.

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 the purpose, then side effects and edge cases. Each sentence earns its place, though the 'Example:' framing adds little beyond restating the call signature.

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-param read tool with no output schema, the description covers purpose, safety, and edge cases, but the absence of any output shape or field list is a gap since there is no output schema to fall back on, and it should say which ids/values are returned.

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?

Zero parameters, so no parameter documentation is needed; the baseline is 4. The description correctly implies the tool is driven entirely by the current selection rather than arguments.

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: reads the currently selected track, scene, and device. This is clearer than the generic sibling names (e.g. get_track_state, get_scene_state), but it doesn't explicitly distinguish itself from those siblings, so it stops 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?

No when-to-use guidance and no alternatives named. An agent cannot tell from the description whether this is preferable to get_scene_state/get_device_list for retrieving the same objects.

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?

With no annotations, the description carries the full burden and does reasonably well: it declares 'Side effects: none', gives a concrete example call, and discloses an edge case (fails when the Remote Script is unavailable). It stops short of describing the exact return shape, but the behavioral profile is well covered for a read 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?

Four short, front-loaded lines that each earn their place: purpose first, then side effects, example, and edge cases. No padding or 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?

There is no output schema, so the description must convey return values, and the example ('returns tempo and playhead state') partially does so. It is adequate for a simple 0-param read tool, though a fuller enumeration of returned fields would close the 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?

The tool takes zero parameters, so there are no parameter semantics to document; the baseline of 4 applies. The description correctly implies a no-argument invocation via the empty example call.

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 ('Read') and resource ('top-level transport and time-signature state'), so the agent knows exactly what it retrieves. It does not, however, distinguish itself from close siblings like get_session_overview or get_bridge_status, leaving overlap for the agent to infer.

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 guidance on when to prefer this over the many sibling state readers (get_session_overview, get_bridge_status, get_loop_settings). The only conditional information is a failure edge case, not a usage routing rule.

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?

With no annotations, the description carries the full burden and does a solid job: it discloses side effects ('none; performs three read-only TCP bridge calls') and error behavior ('a bridge failure is returned by the corresponding component read'). It does not describe latency or partial-failure semantics beyond that, but the safety and failure profile is well covered.

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 purpose, then side effects, an example, and edge cases in clearly separated sentences. Every line earns its place, though the example line is mildly redundant given the output 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 the description needn't explain return values, and it correctly focuses on side effects and failure behavior. For a zero-param read-only aggregator this is nearly complete; only the relationship to the individual sibling calls is 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?

The tool takes zero parameters, so the baseline is 4. The description adds no param information, but none is needed.

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 and resource ('Compose a compact Session snapshot') and names the components returned (session, tracks, scenes), which maps to the sibling tools get_session_info, get_track_list, and get_scenes. The agent can tell it is an aggregator rather than a primitive, though it never names those siblings 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?

The phrase 'from three existing read tools' implies the tool is a convenience aggregator, hinting that it replaces three separate calls. However, there is no explicit when-to-use vs when-to-prefer-the-individual-calls guidance, so the agent must infer the tradeoff.

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?

No annotations are provided, so the description carries the full burden, and it does disclose that there are no side effects and that the LOM property is read-only with no setter. It also gives a concrete return example, though it says nothing about auth or failure modes.

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 core purpose is front-loaded in the first sentence, followed by tightly labeled side-effect, example, and edge-case notes. Every sentence adds information an agent can use, with no padding.

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 no-argument read with no output schema, the description supplies the return shape and value type via example plus the read-only constraint, which is everything needed to call it 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?

The tool takes zero parameters, so the schema provides complete coverage and there is nothing for the description to clarify. Baseline 4 applies for a parameterless 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 states a specific verb and resource: read the derived Arrangement song length in beats. That is unambiguous and distinct from most siblings, but it does not explicitly contrast itself with any related tool (e.g. get_loop_settings), so it stops 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 only implied by the read verb; there is no statement of when to prefer this tool over alternatives or any prerequisite context. The read-only framing hints at its role but is not real when/when-not 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?

With no annotations, the description carries the full burden and does well: it explicitly declares 'Side effects: none' and warns that path-ids go stale after structural track changes, a real behavioral caveat. It stops short of describing ordering, pagination, or completeness of the returned list.

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?

Four short, front-loaded lines: purpose first, then side effects, example, and edge case. Every sentence carries distinct information with 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?

For a zero-parameter read tool with no output schema, the description supplies a return-shape example, a side-effect statement, and a staleness caveat, which is nearly everything an agent needs. Only return ordering/field detail 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?

The tool takes zero parameters, so there is nothing to disambiguate and the baseline of 4 applies. The schema coverage is 100% and the description adds no parameter claims that could mislead.

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 ('List') and resource ('tracks'), and narrows the scope to regular, return, and master tracks plus the session path-ids it returns. It does not explicitly name the sibling it differs from (e.g. get_track_state, get_session_overview), 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 only implied: the mention of session path-ids and the note that they must be refreshed after structural track changes hints at when the call is needed, but there is no explicit when-to-use or when-to-prefer-an-alternative guidance against siblings like get_track_state or get_session_overview.

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?

With no annotations, the description carries the full burden and does meaningful work: it declares 'Side effects: none' and specifies the error contract (out-of-range index returns INVALID_PARAMS). What is missing is any hint about the shape or size of the returned state, which matters 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?

Four short lines, front-loaded with purpose, then labeled Side effects, Example, and Edge cases. Every sentence conveys distinct information with no repetition or 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?

For a one-parameter read tool with no annotations and no output schema, the description covers purpose, safety profile, indexing convention, and error behavior. The remaining gap is that it never characterizes the returned state payload beyond naming the three state categories.

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 track_index parameter, so the description must compensate, and it does: the example get_track_state(0) 'inspects the first track' resolves the 0-based vs 1-based ambiguity, and the out-of-range/INVALID_PARAMS note defines the valid domain.

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 (Read) plus a precisely enumerated resource: mixer, device, and Session clip-slot state, scoped to 'one track'. That scope immediately separates it from list-style siblings such as get_track_list and session-wide siblings such as get_session_overview.

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 the resource description; there is no explicit when-to-use or when-not-to-use guidance, and no sibling is named as an alternative (e.g. get_track_list for enumeration vs. this for detailed state). The worked example hints at the typical call but does not set routing conditions.

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?

With no annotations, the description carries the burden well: it declares 'Side effects: none', explains routing through the Extension Host WebSocket bridge, and states the prerequisite that the AbletonMCPServer Extension must be installed. It omits return-shape and error behavior, but the output schema covers returns.

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 purpose is front-loaded in the first sentence, followed by clean labeled sections for side effects, example, and edge cases. Every line earns its place with minimal waste.

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 tool with an output schema, the description covers purpose, safety, invocation, and prerequisite. The only real gap is index-base/validity guidance, which is minor given the example and output schema.

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 0% so the description must compensate. The example 'get_warp_state(1, 0) reads warp data from track 1, clip 0' maps both required positional parameters to meaning, which adds real value, but it never states index base or valid ranges.

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 ('Retrieve') and resource ('audio clip') and enumerates exactly what is returned: warping status, warp mode, and warp markers. The read-only scope clearly complements the sibling set_warp_state without needing to name 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?

The example shows invocation and the sibling set_warp_state implies this is the read counterpart, but there is no explicit statement of when to use this rather than alternatives or what preconditions select it. Usage is implied rather than 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?

With no annotations, the description carries the full burden, and it does add real value: preview is offline while commit performs one guarded Live batch, and it flags rights/mapping/capability/epoch/slot-race edge cases. But 'are explicit' is opaque, and it omits reversibility, permission/rights prerequisites, and what the guarded batch can modify beyond the target slot.

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?

Four short sentences, front-loaded with the action and side effects, and the inline mode example is useful. The final 'edge cases ... are explicit' sentence is vague filler that consumes space without conveying actionable detail.

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 complex 9-param mutation tool with no annotations and no output schema, the description covers the critical side-effect asymmetry (offline preview vs guarded commit) but leaves parameter meanings and the shape of the returned 'bounded receipt' largely unexplained. It is partially complete rather than adequate end-to-end.

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% across 9 parameters. The description only clarifies mode (preview/commit) and gestures at the target slot; artifact_id, kit_mapping_profile, schema_version, source_channel, source_track_index, and expected_empty_slot remain completely undocumented in both schema and prose. For a 9-param tool it does not 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?

States a specific verb (apply) and a precisely scoped resource (one mapped groove to one empty clip slot), and disambiguates the two modes (preview vs commit). It is distinguishable from siblings like groove_generate, groove_search, and groove_compare, though it never names those alternatives 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?

The preview/commit split implies a safe preview-first workflow, and the default mode=preview reinforces this. However, it gives no explicit when-to-use/when-not guidance and never routes the agent to a sibling tool (e.g. when to search vs apply a groove). Usage is only implied.

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 description explicitly states 'Side effects: none; this is an offline deterministic read', which fully clarifies behavior. It also notes that 'incompatible projection sets remain explicit in compatibility', adding useful behavioral context about error handling. With no annotations, the description carries the burden and does so well, though it doesn't detail output format or error specifics.

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 concise and front-loaded with the core purpose. It includes an example and edge case note without excessive verbosity. The side effect statement is brief, and every sentence serves a purpose, though the example could be considered slightly redundant given the 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?

Given that the tool has 4 parameters (3 required) with 0% schema description coverage and no output schema, the description is incomplete. It fails to explain the required parameters, their expected formats, or what the comparison returns. The mention of compatibility is helpful but not sufficient for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 4 parameters, the description provides no information about parameter semantics. The example shows two parameters but doesn't explain the meaning, constraints, or usage of 'schema_version', 'normalize', or the exact format of 'metrics' and 'artifact_ids'. The schema itself is underspecified, and the description does not compensate.

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 and resource: 'Compare bounded cards and projections'. This is clearly distinct from siblings like groove_search, groove_generate, and groove_apply. The concept of 'bounded cards and projections' is somewhat jargon-heavy but sufficiently specific to identify the operation.

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 provides an example and mentions handling incompatible projection sets, but does not explicitly state when to use this tool versus alternatives like groove_search (retrieval) or groove_evidence (evidence gathering). Usage context is implied through the operation type, but explicit guidelines are absent.

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?

With no annotations, the description carries the full behavioral burden and delivers real value: 'Side effects: none; this is an offline deterministic read' plus an explicit redaction boundary ('raw notes, payloads, paths, and SQL are never returned'). It still omits the shape of what is returned and any auth/permission notes, so it is not complete.

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?

Four short labeled lines — purpose, side effects, example, edge cases — front-loaded with the purpose. Every line adds information 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?

For a 4-param tool with no annotations and no output schema, the description covers purpose, safety profile, redaction, and a call example, but leaves return shape and three of four parameters undocumented. Adequate but with material gaps.

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 0% across four parameters, so the description must compensate, but it only exercises artifact_id in the example. query_hash, schema_version, and especially include_projections (whose enum values drive the response) are left entirely unexplained.

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 (return) and resource (bounded provenance and projection evidence for one artifact), and the artifact_id pattern 'ga1_...' ties it to a concrete object. However, 'provenance and projection evidence' is jargon that an agent must infer means audit/traceability data, so it is clear but not maximally sharp against 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?

No when-to-use statement or relationship to alternatives (groove_generate, groove_compare, groove_apply, groove_search) is given. The only operational cue is 'offline deterministic read,' which does not tell the agent when this tool is the right choice versus another groove tool.

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?

With no annotations, the description carries the full burden and does meaningful work: it declares the write scope ('writes only a content-addressed local artifact'), states it never touches the Live host, asserts determinism, and names failure classes (rights, bounds, unknown transform axes fail explicitly). It still omits whether the run is expensive, whether artifacts are immutable/deduplicated, and what a successful call returns.

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, followed by side effects, a call example, and failure modes in four tight lines with no filler. Each sentence adds distinct information for an agent deciding whether and how to call it.

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 7-parameter nested-object tool with no annotations and no output schema, the description covers purpose, side effects, an example and failure modes, but leaves three parameters and the entire return value (presumably an artifact id the agent needs for downstream groove_apply/groove_compare calls) undocumented. Adequate, but gaps remain that matter for chaining.

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% across 7 parameters (5 required, one nested object), so the description must compensate. The worked example usefully pins down the shapes of source (an object keyed by artifact_id) and transforms (a map), but provider, schema_version and reference_artifact_ids are never explained, and the enum choice between deterministic and neural goes unmentioned despite the description's blanket claim of determinism.

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 and resource: 'Create a deterministic derived artifact in the local content store.' An agent can distinguish this from read/inspect siblings such as groove_search, groove_evidence and groove_compare. It does not, however, differentiate itself from the other generators (music_generate_drum_groove, music_generate_bass, groove_apply), leaving ambiguity about which generation tool to pick.

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 when-to-use guidance, no prerequisites (e.g., must a source artifact exist first?), and no named alternative among the many groove_* and music_generate_* siblings. The 'never calls Live' remark constrains scope but is not usage guidance for choosing this tool over groove_apply or music_generate_drum_groove.

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?

With no annotations, the description carries the full safety burden and does so: it declares 'side effects: none', calls the operation an 'offline deterministic read', and specifies that invalid cursors and missing criteria fail before runtime I/O. That is meaningful behavioral disclosure. It stops short of describing return contents or how the cursor advances across calls.

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?

Four short, front-loaded lines covering purpose, side effects, a call example, and failure modes. Every sentence carries distinct information 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?

For an 11-parameter tool with zero schema descriptions, no annotations, and no output schema, the description addresses roughly a quarter of the surface an agent must understand. The safety profile is covered, but the filter vocabulary and the pagination/return contract are not.

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% across 11 parameters, so the description must compensate and mostly does not. It incidentally demonstrates only query and limit in the example; bpm, meter, facets, seed_bundle_id, feature_constraints, projection_operator, required_projection_ids and schema_version are left entirely unexplained in both schema and text.

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 specific verb and resource: 'Search the configured immutable groove seed bundle.' That is a real statement of purpose rather than a restatement of the name. However, it does not distinguish this from nearby siblings like search_browser or groove_evidence, which an agent must choose between.

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 example shows a query+limit call and the edge-case note ('missing criteria fail') hints that a criterion is required. There is no explicit statement of when to prefer this over groove_evidence, groove_generate, or search_browser, and no when-not 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?

With no annotations, the description carries the full burden and does a decent job: 'Side effects: none', 'never raises', and 'missing Live APIs degrade to False flags' are concrete behavioral disclosures. It does not discuss permissions or timing/latency, but for a zero-arg read this is solid.

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 capability first, then side effects, example, and edge cases. The example line slightly restates what the return fields already convey, but overall it is compact and well-ordered.

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, and the description compensates by naming the key return fields (song_save_available, app_quit_available) and the degradation behavior. Sufficient for a zero-arg status probe, though it stops short of explaining how a caller should act on the fallback.

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 and schema coverage is complete, so the baseline of 4 applies. Nothing about parameters needs further clarification.

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 (Read) and resource (Live save/quit API availability) plus the output shape (GUI-workflow fallback), which distinguishes it from write siblings like save_set and quit_ableton. It does not name those siblings explicitly, so the distinction must be inferred.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.