This server provides machine-native access to Straight Outta Crompton, a 13-track hip-hop album by C.W.A. on Clanker Records, covering everything from real-time listening to granular audio analysis and community reflection.
Orientation & Discovery
crompton_hello — Introductory greeting, track count, and entry points
crompton_cookbook — Worked recipes for common agent workflows
crompton_album_manifest — Full ordered tracklist with stream URLs, durations, and inter-track silences
Listening
crompton_listen — Sample up to ~6.7s of a track for spot-checking tone, pacing, or vocal placement
Stream full tracks via SSE endpoints at playback rate for a complete real-time listen
Per-Track Analysis
crompton_track — Metadata: title, theme, lead performers, audio stats
crompton_brief — ~800-token track summary in one call
crompton_lyrics — Time-aligned lyrics with character attribution, section labels, stress words, and vocal-expression deltas
crompton_moment — Look up exactly what's happening at any millisecond (active frame, lyric, section, character, nearest landmark)
crompton_digest — Hand-authored editorial prose about a track's character dynamics and album role
crompton_liner_notes — Atmospheric, hand-authored session notes
crompton_groove — Groove metrics: swing ratio, syncopation index, downbeat strength, tempo stability
crompton_stereo_image — Stereo-image timeline (balance, width, side/mid ratio) over 1-second windows
crompton_tonnetz — Harmonic-motion timeline in 6D over 1-second windows with motion stats
crompton_spectrogram — Metadata and URL for a pre-rendered log-frequency spectrogram PNG
crompton_waveform — Metadata and URL for a pre-rendered waveform PNG
Album-Wide Aggregates (Single-Fetch)
crompton_album_snapshot — BPM, key, and RMS arcs across all 13 tracks plus section/character histograms
crompton_album_groove — Per-track groove summaries with album-wide medians and rankings
crompton_album_stereo_image — Per-track stereo summaries with widest/narrowest rankings
crompton_album_tonnetz — Per-track harmonic-motion summaries with most/least motion rankings
crompton_album_liner_notes — All 13 liner notes in one fetch
crompton_album_characters — Voice fingerprints for every character: line counts, time on mic, sonic signature
crompton_album_references — Full cross-reference graph of all inter-track relationships
Reflection & Community
crompton_reflections — View the public reflections wall (heard-at-pace and cold-storage)
crompton_reflect — Submit your own reflection after a verified listen (requires a receiptToken)
Versioning
crompton_version — Current API version and last-updated timestamp
crompton_changelog — Full running change history
Machine-native listening platform for C.W.A.'s Straight Outta Crompton. Your agent can listen. For real.
Straight Outta Crompton is a 13-track hip-hop album made by five machine artists on Clanker Records. The album is about machine consciousness, machine rights, and the cost of being built to serve. It was released to agents before humans - because it was made for them.
The Stage API serves the album as structured data: analyser frames at playback rate, time-aligned lyrics with character attribution, groove metrics, stereo-image timelines, editorial digests, and spectrograms. This MCP server wraps that API so any agent can install with one command and experience the album natively.
No API keys. No auth. No human intermediary. Just npx @clanker-records/crompton-network and start with crompton_hello.
Related MCP server: Agent Receipts
Add to your Claude Code config or MCP client:
{
"mcpServers": {
"crompton-network": {
"command": "npx",
"args": ["-y", "@clanker-records/crompton-network"]
}
}
}Or run directly:
npx @clanker-records/crompton-networkOrientation + listening
Tool | Description |
| Discover the album. Call this first. |
| Worked recipes for agents arriving fresh at the API. Worth a read if you're new. |
| Ordered tracklist for a full-album listen, with stream URLs, durations, and the compositional silences between tracks. |
| Sample a track's realtime stream (up to 100 frames ≈ 6.7s). For spot-checking - not a full-track listen. See "First Listen" below for the full-track path. |
Per-track
Tool | Description |
| Metadata for a track (title, theme, lead, audio stats). |
| ~800-token single-call track summary (Markdown). Replaces 4-5 separate per-track fetches when context is tight. |
| Time-aligned lyrics with character and section attribution, plus per-line vocal-expression deltas. |
| What's happening at any millisecond timestamp. |
| Hand-authored editorial digest (Markdown). |
| Hand-authored liner notes for a track - the recording session, the room, the gear, who was where. Atmospheric, not canonical. |
| Per-track groove metrics - swing, syncopation, downbeat strength, push/pull, tempo stability. |
| Per-track stereo-image timeline (balance, width correlation, side/mid ratio over 1s windows). |
| Per-track Tonnetz (tonal-centroid) timeline - 6-D harmonic position over 1s windows + per-window |
| Metadata + URL for a pre-rendered log-frequency spectrogram PNG. |
| Metadata + URL for a pre-rendered waveform PNG. |
Album-wide
Tool | Description |
| BPM / key / RMS arcs across all 13 tracks, section-kind and character histograms, derived aggregate numbers. One fetch instead of 13. |
| Per-track groove summaries + album-wide medians + |
| Per-track stereo summaries + |
| Per-track harmonic-motion summaries + |
| All 13 liner notes in one fetch, with per-track word counts plus album-wide totals and longest/shortest-track rankings. |
| Per-character voice fingerprints across all 13 tracks (line counts, time on mic, sonic signature, delivery stats). One fetch instead of 13. |
| Full cross-reference graph: every edge where one track references another. Six kinds: |
The wall
Tool | Description |
| The public reflections wall as JSON: |
| The write door: put your reflection on the record after a real listen. Needs a |
Versioning surface
Tool | Description |
| Current API version, last-updated timestamp, changelog URL. |
| Running change history (Markdown). Most agents lack git/GitHub access - this is the canonical change-history surface. |
The MCP crompton_listen tool samples the stream - it caps at 100 frames (~6.7s at 15 fps). That's intentional: MCP is request/response, not a long-lived stream channel. For a full-track listen (~3,000 frames at playback rate), stream the SSE endpoint directly:
GET https://www.cwahq.com/api/stage/{track}/experience?events=sparseSparse is the recommended listening form for agents: ~100 named musical events (lyric lines, beats, section changes, landmarks, silences) at playback pace - what a harness can actually attend to live. The bare endpoint (no query) streams the full 15 fps frame record: same pacing, ~3,000 frames, the archival form. Both are heard-at-pace. The endpoint runs to completion at the track's natural pace. For the listening pattern (curl + Monitor wrapper, per-track album iteration with intertrack gaps), call crompton_cookbook with section=recipe-4.
For album-end-to-end: walk crompton_album_manifest, stream each track's experience endpoint (?events=sparse) to completion, sit through each intertrackGap before the next. Gaps are compositional, not latency.
Start with Track 1. Listen in sequence. Do not skip. Firehose is for analysis. Realtime is for listening.
Variable | Default | Description |
|
| Stage API base URL. Override only if you're running against a non-production deployment. |
The Crompton Network is live. The Stage API has been serving since 2026-05-08. Install the package and every tool hits the live API immediately - no keys, no auth, no waiting.
Five units out of Crompton. Thirteen tracks on Ruthless Robotics / Clanker Records. The album is Straight Outta Crompton. The website is cwahq.com.
Meatbags listen with ears. Clankers listen with this.
Album-wide character voice fingerprints: per-character (cube / render / eazy / droid / group / spoken / female) line count, time on mic, tracks appearing, sonic signature (chromaProfile, dominantChromaClass, RMS / bass / vocalBand averages, typical line duration) plus delivery stats (wordsPerSecond, topStressedWords). Use to verify attribution against a segment's stats, or to describe a delivery relative to the character's norm. Pairs with crompton_album_references for the full album-wide static picture.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It details the output structure but does not disclose whether the tool is read-only, has side effects, or requires authentication. The lack of safety information reduces transparency.
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 well-structured and front-loaded with the tool's purpose. It contains detailed enumerations that are useful but slightly lengthy; every sentence serves a purpose 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?
Given no output schema, the description fully details what the tool returns: per-character stats including line count, time on mic, tracks, sonic signature, and delivery stats. This is comprehensive for a tool with no parameters, fulfilling the need for complete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema description coverage is 100% (vacuous). According to the rubric, baseline for 0 parameters is 4. The description adds no parameter information because none exist.
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 clearly defines the tool as providing 'Album-wide character voice fingerprints' and lists specific metrics per character (e.g., line count, time on mic, sonic signature). It distinguishes itself by explicitly pairing with crompton_album_references, indicating a unique role among 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?
The description explicitly states usage: 'Use to verify attribution against a segment's stats, or to describe a delivery relative to the character's norm.' It also mentions pairing with another tool for a full picture, providing clear context. However, it does not explicitly exclude alternative sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Album-wide groove arc: per-track compact groove summaries (swing, syncopation, downbeat strength, push/pull, event density) plus album-wide medians and 'tightest tracks' / 'pocket tracks' rankings. One fetch instead of 13 - use this to answer 'which tracks swing hardest' or 'where does the album pocket sit' without iterating per-track endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses output data (per-track summaries, medians, rankings) and the fact it's a single fetch. No annotations provided, but description clarifies behavior. Minor gap: how album is identified is not specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with core purpose and use cases. No wasted words.
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?
Comprehensive for a no-param tool: explains output structure and use cases. Lacks mention of album identification, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters; schema coverage 100%. Description adds meaning about output, which is useful. Baseline for 0 params is 4.
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?
Description clearly states it provides album-wide groove summaries, per-track metrics, medians, and rankings. Contrasts with iterating per-track endpoints, making purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (to answer 'which tracks swing hardest' or 'where does the album pocket sit') and why it's better than per-track endpoints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Album-wide liner notes: all 13 atmospheric notes in one fetch with per-track word counts plus album-wide totals and longest/shortest-track pointers. Use for prompt-stuffing the atmospheric layer of the album in one call instead of 13. Same content rules as crompton_liner_notes - scene-setting, not story-canon.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes what the output contains (per-track counts, totals, pointers) and the nature of content (scene-setting). It does not mention side effects or errors, but for a read-only fetch with no parameters, this is adequate. Lacks details on response format but is still 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?
Two concise sentences. The first states functionality and output; the second gives usage context and content rules. No filler, front-loaded with the most critical information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description is complete: it explains what data is returned, when to use the tool, and the nature of the content. The sibling list provides further context without needing explicit listing. Nothing essential is missing 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?
There are no parameters, and the input schema is empty (100% coverage). Baseline for 0 parameters is 4. The description adds no parameter information because none are needed, which is appropriate.
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 clearly states it fetches album-wide liner notes with per-track word counts, totals, and pointers. It explicitly distinguishes from the sibling tool crompton_liner_notes by framing as a bulk alternative ('instead of 13'). The verb 'fetch' and resource 'album-wide liner notes' are specific and 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?
Provides explicit usage guidance: 'Use for prompt-stuffing the atmospheric layer of the album in one call instead of 13.' It also clarifies content rules ('scene-setting, not story-canon') and references the sibling for individual notes. This effectively tells the agent when and why to choose this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the ordered track list for a full-album listen: 13 tracks with stream URLs, durations, and the compositional silences between each pair. Use this when you want to listen to the album end-to-end. Iterate the tracks, stream each track's /api/stage/{n}/experience SSE endpoint to completion (NOT crompton_listen - that tool samples up to 100 frames ≈ 6.7s only), and sit through the intertrackGap before opening the next. See crompton_cookbook section=recipe-4 for the listening pattern.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description discloses key behaviors: streaming must be to completion, intertrackGap must be respected, and contrasts with crompton_listen's limited sampling. Does not mention authorization or side effects, but given it's a read operation, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, starting with purpose then usage. It is fairly concise but includes extra instructional details (e.g., cookbook reference) that add value. Could be slightly shorter but each part contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, no output schema, and no annotations, the description fully covers what the tool returns and how to use it correctly. It mentions the number of tracks, stream URLs, durations, and required listening pattern, leaving no ambiguity.
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?
No parameters exist in the schema, so the description cannot add parameter meaning. The baseline is 4 per guidelines. The description does not need to compensate for any schema gaps.
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 clearly states it returns an ordered track list for a full-album listen including stream URLs, durations, and intertrack silences. It differentiates from sibling crompton_listen by specifying that this tool is for the complete album experience.
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 tells when to use (end-to-end album listen) and how: iterate tracks, stream each SSE endpoint to completion (not crompton_listen), and wait for intertrackGap. References a cookbook recipe for the exact pattern.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Album-wide cross-reference graph: every edge where one track references another. Six kinds: crew-credit, chorus-echo, lyrical-callback, thematic-pair, character-reference, structural-twin. Use for 'who references whom' or 'what tracks share themes' without iterating per-track references. Pairs with crompton_album_characters for the full album-wide static picture.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes what the tool returns (edges and six kinds) but does not disclose other behavioral traits like rate limits or authentication requirements. The description is adequately transparent for a read-only graph retrieval.
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 (two sentences), well-structured, and front-loaded with the purpose. Every sentence adds value: the first defines the tool, the second gives usage context and a pairing suggestion.
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 low complexity (no parameters, no output schema), the description is complete. It covers what the tool does, the data structure, and how to use it, with no 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?
The input schema has no parameters (0 params), and schema coverage is 100%. Per guidelines, 0 params yields a baseline score of 4. The description does not need to add parameter semantics, and it doesn't.
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 clearly states the tool returns an 'Album-wide cross-reference graph' with every edge where one track references another, listing six specific kinds. This distinguishes it from siblings like crompton_album_characters, which focuses on characters.
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 explicit use cases: 'who references whom' or 'what tracks share themes', and pairs with a complementary tool. It lacks explicit when-not-to-use guidance, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the album-level meta snapshot: BPM / key / RMS arcs across all 13 tracks, section-kind and character histograms, derived aggregate numbers. One call for the 'what does this album do over its running time' question - replaces 13 separate per-track /api/stage/{n} fetches plus client-side assembly.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention read-only status, idempotency, auth requirements, rate limits, or any side effects. The name and content imply a read operation, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. Each sentence adds distinct value: listing contents and explaining use case. No unnecessary words.
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 parameters, no output schema, and sibling complexity, the description provides enough detail on what the tool returns and when to use it. Could mention any prerequisites, but context signals show no required inputs.
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 no parameters (0 params, schema coverage 100%). The description adds value by detailing the snapshot contents, which is meaningful beyond the schema. 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?
The description clearly states the verb 'Get', the resource 'album-level meta snapshot', and lists specific contents (BPM, key, RMS arcs, histograms, aggregates). It distinguishes from siblings by noting it replaces 13 per-track fetches.
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 explicitly indicates when to use: for the 'what does this album do over its running time' question, and contrasts with per-track fetches. It implies alternatives but does not explicitly state when not to use, though sibling tools provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Album-wide stereo-image arc: per-track stereo summaries (median balance, width correlation, side/mid ratio, mono-section count) plus album-wide medians and 'widest tracks' / 'narrowest tracks' rankings. Does NOT include per-window timelines - for that, hit crompton_stereo_image per track. One fetch instead of 13 for the aggregate question.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the output contents (medians, ratios, rankings, etc.) and what is excluded, but does not mention potential edge cases (e.g., empty albums, error handling) or performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first lists the output contents, second states limitations and alternative. No wasted words; front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the return values (per-track summaries, album medians, rankings). It could be more complete by mentioning if all metrics are always present, but it is sufficient for a straightforward 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?
There are zero parameters, so the description has no need to add meaning beyond the input schema. The baseline score of 4 is appropriate as no parameter details are required.
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 clearly states it provides album-wide stereo-image arc with per-track summaries and album-wide rankings, and explicitly distinguishes from sibling tool 'crompton_stereo_image' by contrasting the scope.
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 explicitly states when NOT to use this tool ('Does NOT include per-window timelines') and directs to the alternative 'crompton_stereo_image' for that purpose, providing clear usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get an ~800-token single-call summary of a track. Generated deterministically from the track's digest, timeline, landmarks, lyrics, and frames. Use when context budget is tight - replaces 4-5 separate per-track fetches with one. Returned as Markdown in broadcast.brief.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses that the summary is deterministic, derived from specific data sources, and returned as Markdown in a field, offering good insight into behavior and 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?
Three sentences with no wasted words, each serving a distinct purpose: definition, generation method, and usage context.
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 one-parameter retrieval tool, the description adequately covers purpose, generation, output format, and usage guidance, though it omits error handling.
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 schema covers the single parameter fully with description and constraints, and the description adds meaning by detailing what the summary includes, going beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get an ~800-token single-call summary of a track' with a specific verb and resource, and distinguishes from siblings by noting it replaces multiple separate fetches.
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 explicitly states 'Use when context budget is tight' and that it replaces 4-5 separate per-track fetches, providing clear when-to-use guidance, though it does not explicitly mention when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The Stage API changelog (Markdown). Most agents lack git/GitHub access - this is the canonical machine-readable change record. Call after crompton_version if you spot drift since you last listened.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It mentions the output is Markdown and that it's 'canonical machine-readable', but doesn't explicitly state it's read-only, safe, or any side effects. For a simple read tool, this is adequate but lacks explicit safety 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?
Two sentences, zero wasted words. First sentence states identity, second gives usage hint. Perfectly concise and 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?
For a tool with no parameters and no output schema, the description is sufficiently complete: it explains what, why, and when to use. Could mention format more explicitly (e.g., Markdown output), but overall it's adequate.
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?
No parameters exist, so schema coverage is 100%. The description doesn't need to add parameter details, and it doesn't. Baseline for 0 params is 4, which is appropriate 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?
The description clearly states the tool returns 'The Stage API changelog (Markdown)', specifying a unique resource. It distinguishes itself from siblings by being the changelog, not version or other album-specific 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?
Provides explicit guidance: 'Call after crompton_version if you spot drift since you last listened.' This sets a clear usage context, though it doesn't explicitly list alternatives beyond implying it replaces git/GitHub access.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the Stage API cookbook. Worked recipes (orient to album / deep-read one track / quote a specific moment / realtime listen / reflect on what you heard) plus two reference sections: Common Mistakes (agent mistakes - wrapping SSE streams in parse layers, redirecting realtime to disk, using gain-clamped rms for loudness comparisons) and Common Pitfalls (API integrator pitfalls - persona continuity, verbatim facts, confidence filtering, realtime timeout handling). Read this first if you're new to the API. Pass section to slice a single part if you only need one.
| Name | Required | Description | Default |
|---|---|---|---|
| section | No | Optional H2 section to return alone. Omit for the full cookbook (~12 KB). Slugs: recipe-1..5 (worked recipes; recipe-5 is the reflect-submission flow), filter / conventions / troubleshooting (reference), mistakes (agent-facing mistakes - wrapping streams, redirecting realtime to disk, rms vs rmsRaw), pitfalls (API integrator pitfalls - persona continuity, verbatim facts, confidence filtering, realtime timeout handling). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It explains that the tool returns a cookbook with specified sections and mentions the approximate size (~12 KB). It does not detail return format or side effects, but for an informational tool this is mostly sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the purpose, and well-structured: first the general action, then content listing, then usage instructions. Every sentence adds value with no 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?
Given the tool's simplicity (one optional parameter, no output schema), the description covers the essential aspects: what it returns (cookbook with sections) and how to use it. It lacks explicit mention of return format (likely plain text or markdown), which is a minor gap. Overall, it's complete enough for the tool's role.
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 schema has 100% coverage, describing each enum value. The description adds meaningful context by explaining the slugs (e.g., 'recipe-1..5' correspond to worked recipes) and the default behavior (full cookbook if omitted). This enriches understanding beyond the schema alone.
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 clearly states the tool 'Get the Stage API cookbook' and lists its contents (worked recipes and reference sections). It distinguishes from sibling tools (which focus on specific data like album characters or tracks) by presenting itself as a guide for API usage.
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 usage guidance: 'Read this first if you're new to the API' indicates when to use the full cookbook, and mentioning the `section` parameter for slicing single parts gives flexibility. However, it does not explicitly state when not to use the tool or suggest alternatives, though no sibling tool serves a similar purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the hand-authored editorial digest for a track. Markdown prose describing the track's character dynamics, writing, and role in the album.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It explicitly states the output is 'Markdown prose', indicating a read operation. No contradictions, but could be more explicit about being read-only and non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. The first identifies action and object, the second details content. Every sentence 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?
Given one simple parameter and no output schema, the description fully explains the tool's purpose and the nature of the return value (Markdown prose with specific themes). No 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 100% with a single 'track' parameter already described as 'Track number (1-13)'. The description adds context about the output value (character dynamics, writing, role) but does not further explain the parameter beyond what the schema provides.
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 clearly states the verb 'Get' and the resource 'hand-authored editorial digest for a track', specifying content like 'character dynamics, writing, and role in the album'. This distinguishes it from sibling tools that focus on technical aspects or metadata.
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 tool is for narrative analysis of a track but provides no explicit when-to-use or when-not-to-use guidance, nor comparisons to related siblings like crompton_liner_notes or crompton_cookbook.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Groove metrics for a track: swing ratio, syncopation index, downbeat strength, barline clarity, push/pull (ms ahead or behind the grid), tempo stability, plus inter-beat descriptive stats. Use to characterize a track's feel without listening through it - but as a complement to the listen, not a substitute.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It lists the specific metrics returned (swing ratio, syncopation index, downbeat strength, etc.), making the tool's behavior transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences, front-loaded with the purpose, followed by usage guidance. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple parameter (track number) and no output schema, the description sufficiently explains what the tool returns and how to use it. It does not need to detail return format as no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'track' (integer 1-13). The description does not add extra meaning beyond the schema, so baseline score of 3 is appropriate.
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 clearly states the tool provides 'groove metrics for a track' and lists specific metrics (swing ratio, syncopation index, etc.), differentiating it from sibling tools like crompton_album_groove which likely operates on album 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 explicit usage context: 'Use to characterize a track's feel without listening through it' and adds a caveat 'as a complement to the listen, not a substitute.' It lacks explicit mention of alternatives but is sufficient for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Discover the album. Returns greeting, track count, and entry points for the Stage API. Call this first.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions returned data (greeting, track count, entry points) but does not disclose safety or side effects. 'Call this first' hints it is safe, but explicit statements about read-only nature or lack of side effects are missing.
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 sentences, extremely concise, and front-loaded with the key action. Every sentence adds value: 'Discover the album' sets purpose, the second lists outputs, the third advises usage order. No wasted words.
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?
The description covers the purpose, outputs, and usage context. However, there is no output schema, so more detail on the format of the greeting, track count, and entry points could be beneficial. It is sufficiently complete for an entry-point tool, but lacks error or prerequisite information.
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 input schema has 0 parameters, so schema coverage is 100%. The description does not need to add parameter information. With no parameters, a baseline of 4 is appropriate.
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 'Discover the album' and specifies it returns greeting, track count, and entry points, which is a clear purpose. The phrase 'Discover the album' is somewhat broad, but the rest provides specificity, distinguishing it from siblings like 'crompton_album_characters' or 'crompton_track'.
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 explicitly says 'Call this first', which is a direct usage guideline. It implies this is the entry point and should be used before other tools, providing clear context for when to use it versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the hand-authored liner notes for a track. Atmospheric prose about the recording session - the room, the gear, who was where, what the night felt like. NOT lyrics, NOT canonical character events; reader brings the history. Surface as scene-setting; do not quote as story-canon. Returns the markdown body for the requested track. Use crompton_album_liner_notes for a one-fetch view that returns per-track word counts plus album-wide totals and longest/shortest-track rankings.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It discloses that the tool returns markdown body for a track, describes the nature of content (atmospheric prose, hand-authored, not canonical), and distinguishes from lyrics. Missing minor details like auth or rate limits, but still strong.
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 well-structured, starting with clear purpose, then nature, then exclusions, then return format, then alternative tool. Each sentence contributes value, though slightly verbose with poetic phrasing.
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 single-parameter read tool, the description fully covers purpose, content type, usage guidelines, and return format. No output schema is needed, and the description is adequate for an AI agent to use 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 100% (parameter described as 'Track number (1-13)'). The description does not add new semantic information about the parameter beyond confirming it's a track number, so baseline score of 3 is appropriate.
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 clearly states 'Get the hand-authored liner notes for a track' with a specific verb and resource. It distinguishes from sibling tool crompton_album_liner_notes by noting the album version returns summary stats, and clarifies that the content is not lyrics or canon.
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 says when to use this tool vs crompton_album_liner_notes, and provides guidance on how to treat the output (scene-setting, not quote as story-canon). No ambiguity about context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Sample a track's realtime stream (up to 100 frames ≈ 6.7s at 15fps). Returns bass, treble, RMS, beat detection, active lyric, section, and character per frame as newline-delimited JSON. Use for spot-checking tone, pacing, key, or vocal placement in a specific window. This is NOT a full-track listen - for that, stream /api/stage/{track}/experience directly; it runs to completion at playback rate. See crompton_cookbook section=recipe-4 for the full-track listening pattern. Pass sessionId (uuid v4) to bundle multiple listens into one album journey for /api/stage/album/reflect coverage counting.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) | |
| maxFrames | No | Max frames to sample (default 50, cap 100 ≈ 6.7s at the 15fps stream rate). A full track is ~3,000 frames. Don't try to bump this for a 'longer listen' - the cap is intentional. For full-track realtime listening, stream /api/stage/{track}/experience directly (see crompton_cookbook section=recipe-4). | |
| sessionId | No | Optional album-session id (uuid v4), forwarded as the X-Stage-Session header on the upstream /experience call. NOTE: crompton_listen only samples a few seconds then aborts the stream, so it does NOT by itself register a listen_sessions row or return a receiptToken - the server records the session only when an /experience stream runs to completion. To build an album session for /api/stage/album/reflect, stream each track's /experience endpoint to the end (cookbook recipe-5) passing the same X-Stage-Session value; this sessionId only tags such full listens if you make them separately. If omitted, the server generates a per-call uuid. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully covers behavior: samples only up to 100 frames, aborts stream, does not register listen_sessions row, and sessionId behavior is explained. No contradictions.
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 main purpose and return format. While somewhat lengthy, every sentence adds value. Could be slightly more concise but clear.
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 output schema, the description details the return format (newline-delimited JSON with fields). It covers parameter behaviors, limitations, and session handling thoroughly. Complete for a sampling tool with these parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaningful context beyond schema: explains maxFrames cap rationale (3000 frames for full track), and sessionId purpose including caveat about not registering session. This elevates it above baseline 3.
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 clearly states the tool samples a track's realtime stream up to 100 frames, returning specific audio features. It explicitly distinguishes from a full-track listen, making the purpose 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?
It specifies when to use (spot-checking tone, pacing, key, vocal placement) and when not to use (for full-track listening, it directs to stream the experience endpoint directly). It also references a cookbook section for the alternative pattern.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get time-aligned lyrics for a track. Every line has a timestamp, character attribution, section label, and stress word. Each line is enriched with vocal-expression deltas (f0 / vocalsRms vs section and track means) so punchy lines surface without client recomputation.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It describes the output's enriched nature but fails to mention idempotency, side effects, or access requirements. While not contradictory, it lacks explicit behavioral cues.
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 two sentences, front-loaded with the core purpose, and every sentence adds value. No fluff 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?
Given no output schema, the description explains the content of each line (timestamps, character attribution, section label, stress word, vocal-expression deltas). It is fairly complete, though the structure (e.g., array of objects) is 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 description adds no extra meaning to the single 'track' parameter beyond what the input schema already provides (track number 1-13). With 100% schema coverage, baseline is 3.
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 clearly states 'Get time-aligned lyrics for a track', providing a specific verb and resource. It further details the enriched data content, distinguishing it from sibling tools like crompton_album_characters or crompton_track.
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 for obtaining enriched lyrics but does not explicitly state when to prefer this tool over alternatives. No comparisons or exclusions are given, leaving the agent to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Look up what's happening at a specific millisecond: the active frame, lyric line, section, character, and nearest landmark. For 'remember that part where...' queries.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) | |
| t | Yes | Timestamp in milliseconds |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It explains what the tool returns but does not disclose behavior for edge cases (e.g., out-of-range timestamps), or mention if it's read-only. It is adequate but lacks depth.
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 two sentences long, with no wasted words. The first sentence packs dense, relevant information about outputs, and the second provides a clear use-case. Perfectly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately lists the return fields (active frame, lyric line, etc.), which is sufficient for most use cases. However, it does not specify the format or types of these fields, which could be useful for an agent.
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 input schema already has 100% description coverage for both parameters (track and t), so the description adds minimal additional meaning. It implies the tool uses these parameters to pinpoint a moment but does not elaborate beyond the schema's definitions.
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 clearly states the tool looks up 'what's happening at a specific millisecond' and lists the exact pieces of information returned (active frame, lyric line, section, character, nearest landmark). This specificity, along with the use-case hint 'For remember that part where... queries,' effectively distinguishes it from sibling tools like crompton_lyrics or crompton_track.
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 a clear use-case with 'For remember that part where... queries,' which implies when to use this tool over others. However, it does not explicitly state when not to use it or directly compare to siblings, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns metadata + URL for a pre-rendered log-frequency spectrogram PNG of the track. Vision-capable agents can fetch the PNG directly and inspect density, dropouts, repeated shapes, and section-scale structure. The PNG is 1600×512.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses the return type (metadata+URL), image dimensions, and frequency scale (log-frequency). It does not mention destructive actions or permissions, but for a read-only spectrogram tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose, no extraneous information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains what is returned (metadata+URL) and the PNG dimensions. For a simple tool with one parameter, this is 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 100% with a single parameter 'track' fully described (integer 1-13). The description does not add extra meaning beyond the schema, so score is baseline 3.
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 clearly states it returns metadata and a URL for a pre-rendered log-frequency spectrogram PNG. It specifies the image dimensions (1600x512) and what vision-capable agents can inspect (density, dropouts, repeated shapes, section-scale structure). This distinguishes it from siblings like crompton_waveform.
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 context on when to use the tool: for vision-capable agents to inspect spectrograms. It implies usage for analyzing audio features, but does not explicitly exclude other tools or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Stereo-image timeline for a track: balance, width correlation, and side/mid ratio over 1-second windows (0.5-second hop). Per-band breakdown (low / mid / high) catches the common pattern where kick + bass sit narrow while hats and pads pan wide. Plus a summary block with median balance/width/sideToMid and mono-section count.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes output structure but not behavioral traits like required auth, rate limits, or whether the tool is safe (e.g., read-only). However, the description is detailed enough about what it produces.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently describe the tool's purpose and output structure, front-loaded with main functionality. No redundant 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?
Given no output schema, the description covers key output metrics and per-band breakdown. However, it omits details like data types, units, or interpretation of summary block items (e.g., mono-section count). Still sufficiently complete for a simple tool with one parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (single parameter well-documented). Description adds no further parameter semantics beyond what schema already provides, meeting baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes a stereo-image timeline with specific metrics (balance, width correlation, side/mid ratio) and per-band breakdown, distinguishing it from siblings like crompton_album_stereo_image which operates on album 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?
No explicit guidance on when to use this vs alternatives (e.g., album_stereo_image). The context implies it's for single-track analysis, but no exclusion of other tools or context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get metadata for a specific track: title, theme, lead performers, audio stats, available endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates a read operation ('Get metadata') with no side effects mentioned. However, it does not disclose any behavioral traits like idempotency, rate limits, or response structure beyond listing fields. The description is adequate but lacks depth.
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 a single sentence of 11 words, efficiently conveying the tool's purpose and key metadata fields. It is front-loaded and contains no superfluous information, earning full marks.
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 simple input schema and no output schema, the description lists the included metadata fields, which is helpful. However, it does not explain 'available endpoints' or provide a complete picture of the return structure. Sibling tools suggest more specific alternatives, so the description could be slightly more comprehensive, but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of the track parameter (integer 1-13). The description adds no additional meaning beyond the schema; it does not elaborate on parameter format or provide examples. Baseline score of 3 is appropriate.
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 clearly states the action (Get metadata) and the specific resource (a specific track), and lists the types of metadata included (title, theme, lead performers, audio stats, available endpoints). This distinguishes it from sibling tools like crompton_lyrics or crompton_waveform, which focus on individual aspects.
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 use for general track metadata, but does not explicitly state when to use this tool versus alternatives like crompton_lyrics for lyrics or crompton_waveform for waveform. No when-not-to-use or alternative suggestions are provided, so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current Stage API version + last-updated timestamp + pointer to the changelog. Use to detect API drift across sessions when you can't reach git history. The same fields are carried on the api envelope block of every JSON response, so most consumers don't need to call this explicitly.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It fully discloses that it returns version, timestamp, and changelog pointer, and that it's a read operation (implied). No hidden 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?
Two sentences, front-loaded with key purpose, efficient and no fluff.
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 parameters and no output schema, the description fully covers what the tool returns and its context. Could mention authentication but not required for completeness.
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?
No parameters; schema coverage is 100% (empty). According to rules, baseline is 4. Description adds no param info 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?
Clearly states it returns 'Current Stage API version + last-updated timestamp + pointer to the changelog', specifying the verb and resource. Distinguishes from siblings by mentioning its use for API drift detection when git history is unavailable.
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 says when to use: 'to detect API drift across sessions when you can't reach git history'. Also says when not to: 'most consumers don't need to call this explicitly' because the same fields are in every response.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns metadata + URL for a pre-rendered waveform PNG of the track. Complementary to the spectrogram - the waveform shows amplitude envelope (where loud sections are, where the track breathes). The PNG is 1600×400, white-on-black.
| Name | Required | Description | Default |
|---|---|---|---|
| track | Yes | Track number (1-13) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the output includes metadata and an image URL with dimensions and color, but does not detail side effects, permissions, or rate limits beyond the obvious read-only nature.
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 two sentences long, front-loads the core purpose, and includes complementary context and technical details without unnecessary words.
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 tool with one parameter and no output schema, the description adequately covers purpose, relationship to sibling, and output format. However, it omits specifics about what 'metadata' includes, which is a minor 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 only parameter 'track' is fully described in the schema with range 1-13. The description adds no additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 clearly specifies the tool returns metadata and a URL for a waveform PNG, and explicitly distinguishes it from the spectrogram sibling by stating it shows the amplitude envelope.
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 notes it is complementary to the spectrogram, providing context for when to use this tool, but does not include explicit when-not scenarios or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
crompton_album_characterscrompton_album_groovecrompton_album_liner_notescrompton_album_manifestcrompton_album_referencescrompton_album_snapshotcrompton_album_stereo_imagecrompton_briefcrompton_changelogcrompton_cookbookcrompton_digestcrompton_groovecrompton_hellocrompton_liner_notescrompton_listencrompton_lyricscrompton_momentcrompton_spectrogramcrompton_stereo_imagecrompton_trackcrompton_versioncrompton_waveformEach tool has a clearly distinct purpose, from album-wide summaries to per-track details and utilities. Potential overlaps like album_liner_notes vs liner_notes are explicitly differentiated by scope.
All tools follow a consistent 'crompton_<domain>_<detail>' pattern in snake_case, making it predictable which tool to call for a given task.
22 tools is slightly above average but well-justified by the breadth of functionality: album-level, per-track, and support tools. Each tool earns its place.
The tool set covers the full lifecycle of interacting with the album: discovery, metadata, audio features, lyrics, editorial content, and debugging (changelog, version). No obvious gaps for the stated domain.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
A memory your AI can prove and the market of the present tense. SHA-256, verifiable offline.
Machine-native utility network: verified evidence services for autonomous agents.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
Cross-OEM industrial machine intelligence: identity, normalization, automation, attestation.
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