contest-mcp

Server Quality Checklist

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Latest release: v0.2.1
Disambiguation4/5
Most tools have distinct purposes, but 'status' and 'query' both provide program information, causing slight overlap. Descriptions help disambiguate.
Naming Consistency3/5
Tool names are all lowercase and descriptive, but they lack a consistent pattern (e.g., 'bandmode' vs 'n3fjp_call', no verb_noun structure).
Tool Count5/5
10 tools cover the essential aspects of contest logging without being excessive or insufficient.
Completeness5/5
The surface is comprehensive: status, diagnostics, query, field reading, notifications, logging, band/mode control, search, direct database access, and a raw escape hatch cover all core needs.
Average 4.5/5 across 10 of 10 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 commits in the last 12 weeks
- Last stable release on July 31, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description clarifies it is a non-destructive health check that confirms connection and program loaded, adding useful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with 'Snapshot', providing all key information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description lists the returned fields (program, version, etc.), making the tool's response clear for a simple health check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so baseline 4. The description does not need to add parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a snapshot of program details, version, QSO count, etc. However, it does not explicitly distinguish from the sibling 'diagnostics' tool, which might have overlapping purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as a health check to confirm connection and loaded program, but no explicit when-to-use or when-not-to-use guidance, nor alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It reveals the buffering mechanism and that events aren't streamed in real-time. Missing details on authentication, rate limits, or failure modes, but covers key limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief statement followed by a bullet-like list of operations. It is reasonably concise, though the list could be more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple schema with one parameter and no output schema, the description covers the essential behavior including buffering and operation semantics. Some edge cases (e.g., state after enable) are omitted, but overall complete for a notification management tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'operation' parameter has 0% schema coverage, so the description must fully explain its meaning. It does so by listing the three valid values (enable, disable, drain) and their effects, adding significant value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it manages 'Opt-in push events from N3FJP' with three distinct operations (enable, disable, drain). This specific verb+resource combination distinguishes it from sibling tools like status or query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains when to use each operation and explicitly addresses the request/response buffering limitation, guiding the agent to use drain. However, no explicit when-not or alternatives to other tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lists available operations, adding behavioral context beyond the readOnlyHint annotation. It does not contradict the annotation and provides useful specifics on what queries are possible, though it does not cover rate limits or auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the sentence 'Read-only program queries.' However, the list of operations could be formatted for better readability, but it is still clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description explains what queries are available, it does not specify the format or content of the return values. For a query tool with no output schema, the description could be improved by indicating what each operation returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage (no description) for the only parameter 'operation'. The description compensates by listing all valid operation values, which is critical for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read-only program queries' and lists specific operations like program, qso_count, next_serial, etc. This distinguishes it from sibling tools like status, diagnostics, etc., which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied as read-only queries for program data, but no explicit when-to-use or when-not-to-use guidance is given. Sibling tools exist that could overlap (e.g., status, bandmode), but alternatives are not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation already declares readOnlyHint=true, and the description adds important context: it specifies the three operation modes and warns that derived fields (country_worked, etc.) are computed and should never be written. This goes beyond the annotation, though permissions or side effects are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, using a clear list for operations. Every sentence adds value, and the main purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no output schema, the description covers operations, parameter usage, and a warning. It does not describe the return format in detail except 'with values', but this is sufficient given the low complexity. Could be slightly improved with an example output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 thoroughly explains the 'field' parameter (friendly name or raw control ID, with examples) and the 'operation' parameter (read, visible, all). This adds substantial meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads entry-box text field values and lists three specific operations (read, visible, all). It is a specific verb+resource combination and implicitly distinguishes from sibling tools like status or diagnostics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use each sub-operation (read by field, visible for current fields, all for both visible and hidden). It includes a warning against writing derived fields. However, there is no explicit when-not or alternative comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behaviors: return values (records_added, logged boolean), side effects (dupe creation on retry), conditional execution (calltab=false skips lookups), and reliability notes (trust logged over records_added).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with bullet points for each operation and front-loaded purpose. It is slightly lengthy but every sentence adds value; minor redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, 6 operations, no output schema), the description covers behavior, return values, reliability tips, and contest validation. It lacks explicit error scenarios or full return format details for each operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions (coverage 0%), but the description adds significant meaning for parameters like call, exchange (dict), calltab (default true), and contest. It could still be more systematic in documenting all parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is the headline tool for logging QSOs, enumerates distinct operations (log_qso, set, calltab, etc.), and distinguishes itself from siblings like status and query as the primary logging tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use each operation and includes warnings (e.g., do not retry when logged=true). However, it does not explicitly advise against using this tool for non-logging tasks or when alternatives like search would be better.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does a good job disclosing key behaviors: command normalization, Needs Approval tier, and blocking destructive SQL unless a switch is set. Missing details on error handling or reply format 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and well-structured: one-line purpose, then clear details. Every sentence adds value without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers command usage, safety, and relation to siblings. Missing details on return value structure, but since no output schema, it could be improved. Still sufficient for decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds essential meaning. Explains that 'command' accepts multiple formats and normalizes them, and 'expect' is the response ID to wait for. Additional examples would have made it perfect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is an 'escape hatch' for sending raw N3FJP commands and returning parsed replies. Distinguishes itself from group tools by noting it reaches anything not surfaced by them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (for commands not covered by group tools) and when not to (raw SQL that could wipe database requires a special switch). Provides context on command normalization and authorization tier.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses that it reports resolved N3FJP_HOST/PORT, Python version, hostname, and network interfaces, and importantly states it does not connect to N3FJP. This adds significant behavioral context beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the core purpose, followed by specifics and usage context. No unnecessary words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, but a clear readOnlyHint, the description fully explains the tool's behavior and output. It tells what the tool reports, what it does not do, and provides a use case. Complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description carries the full burden. It describes exactly what the tool reports, which adds all necessary meaning beyond the empty input schema. Baseline for 0 params is 4, and the description exceeds expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs host and network diagnostics for troubleshooting connectivity. It explicitly differentiates from the sibling n3fjp_call by stating it does NOT connect to N3FJP, and the verb 'diagnostics' is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool (troubleshooting connectivity) and what it does not do (connect to N3FJP). However, it does not explicitly list alternatives or when not to use it, though the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description fully carries the burden of disclosing behavior. It details the safety tier (ordinary writes, approval), the hard block for whole-database wipe, and the behavior of each sub-operation (e.g., 'a missing or empty WHERE would clear the whole table').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections, bullet points for operations, and separate warnings. It is organized for readability, though some sentences could be tightened. Overall, it earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, multiple operations, no annotations, no output schema), the description provides comprehensive coverage: it explains all operations, parameter usage, behavioral constraints, and usage guidance. An agent has sufficient information to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 5 parameters with 0% description coverage. The description compensates by explaining the purpose of each parameter in the context of specific operations: e.g., fields for add_direct, where for delete, sql for sql operation, exclude_dupes for add_direct. This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs 'Direct database operations on individual records' and lists specific sub-operations (add_direct, delete, sql, etc.), making the verb and resource obvious. It distinguishes itself from sibling tools like 'log' and 'query' by specifying that it bypasses scoring and allows raw SQL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use alternatives, e.g., 'Prefer log's log_qso/ENTER' for add_direct. It also warns about conditions for safe usage, such as the need for N3FJP_ALLOW_DB_WIPE for destructive operations, and notes that certain operations are blocked without the environment variable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description reinforces 'read-only' and states 'No side effects' for dupecheck. It discloses behavior for each operation (e.g., returns previous contact detail or empty) with 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points and a clear opening sentence. While it is somewhat lengthy due to covering four operations, each section earns its place. A slight reduction in verbosity could improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's 10 parameters and no output schema, the description thoroughly explains all operations, parameter semantics, and behavioral traits. It compares with siblings and covers edge cases (e.g., dupecheck's side-effect-free nature), providing sufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by explaining each parameter's role per operation (e.g., 'count, include_all for list', 'call/band/mode/dxcc/country/confirmed, include_all, max_records for search'). It adds semantic hints like normalizing mode and preferring dxcc over country.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly starts with 'Search and list the log (read-only)' and enumerates four distinct operations (list, search, dupecheck, entity). It explicitly states the tool's scope and differentiates among operations, giving each a concise purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use each operation (e.g., 'Prefer dxcc over country', 'mode is normalized to CW/PH/DIG'). It also directly contrasts dupecheck with the sibling tool's calltab ('No side effects, unlike the log tool's calltab'), offering clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses behavioral traits such as the dependency on rig interface state, the effect of ignore_rig_polls (pausing polling), and the side effect of CW/phone segment flipping. The caution to reset ignore_rig_polls to false shows awareness of state management.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a one-line purpose followed by a clear bullet list of operations. Each sentence adds value without redundancy. The front-loaded purpose and logical grouping make it easy to scan. It is concise yet comprehensive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple operations with conditional behaviors) and lack of output schema or rich annotations, the description is complete. It covers all operations, parameter formats, prerequisites, and a safety note. An agent can confidently invoke any operation based solely on this description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description fully compensates by explaining each parameter's role per operation. It specifies acceptable values for 'value' (e.g., Hz, band like '20', mode like 'DIG') and the meaning of 'suppress_mode_default'. This adds critical semantic context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Change band, mode, and frequency before logging.' It differentiates from sibling tools like 'log' and 'status' by focusing on rig configuration. The verb 'Change' and the specific resources (band, mode, frequency) provide unambiguous purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed usage guidelines for each operation, including conditions (e.g., 'rig interface OFF only' for set_band, 'use suppress_mode_default=true to keep current mode'). It also includes a general caution to ensure correct band/mode before logging. This gives clear when-to-use and how-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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