content-publish-engine-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target distinct actions (preflight, create, run, get, verify, liveness, due-check, auth-probe). However, publish_liveness_check and publish_job_verify both involve verifying published state, which could cause confusion despite differing contexts.
Naming Consistency2/5
Naming is inconsistent: publish_job_create/run/get/verify follow verb_noun, but publish_liveness_check, publish_verification_due, and publish_content_preflight are noun phrases, and platform_auth_probe breaks the publish_ prefix. This mixed pattern reduces predictability.
Tool Count5/5
With 8 tools, the set is well-sized for a content publishing engine, covering the main workflow without being bloated. Each tool addresses a clear step in the process.
Completeness4/5
Core lifecycle (preflight, create, run, verify, liveness) is covered, enabling end-to-end publishing. Minor gaps exist: no job deletion/listing or schedule management, but these are not essential for the stated purpose.
Average 3.4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing side effects and behavioral traits. It states that the tool 'Returns the publish result' and mentions the direct adapter call, but it does not disclose whether this operation is mutating, whether it requires authentication, what happens to the job state, or potential errors. For a tool that 'executes' an action, this is a significant gap.
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 two concise sentences. Both provide distinct, useful information: the action/mechanism and the return value. There is no redundancy or filler, making it appropriately sized for a tool with a single parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema), but the description lacks context about the publish job lifecycle. It does not explain what a 'publish job' is, how this tool fits with siblings like publish_job_create or publish_job_verify, or what 'publish result' entails. The minimal information leaves the agent guessing about the tool's role and expected usage flow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description does not explain the meaning or format of 'jobId'. The tool description only mentions 'one publish job' but never ties it to the parameter. Since the schema does not document the parameter and the description makes no attempt to clarify it, the agent has no guidance beyond the parameter name.
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 action ('Execute one publish job') and the resource ('publish job'), distinguishing it from siblings like publish_job_create, publish_job_get, and publish_job_verify. The phrase 'calling the platform adapter directly' adds specificity about how it executes.
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?
The description implies usage context through the tool name and the phrase 'calling the platform adapter directly,' but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. There is no direct 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the core behavior (liveness check and lifecycle state advancement) but omits key details such as network I/O, failure handling, or the exact state transition. It is not misleading, but it lacks depth about side effects and preconditions.
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 a single well-structured sentence that is immediately actionable. Every word contributes to the core purpose, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a nested object schema and no output schema, the one-sentence description is insufficient. It does not explain the role of the schedule object, define return values, or offer any operational context, making it incomplete for an agent to invoke safely and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain any parameter meaning. jobId and the nested schedule object fields are left entirely to inference, with no help from the text. The description fails to compensate for the missing schema documentation.
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 a specific action ('Check whether an observed public article is still live') and a distinct consequence ('advance its lifecycle state'). This differentiates it from siblings like publish_job_verify or publish_verification_due by emphasizing the liveness check and state transition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention conditions like 'when verification is due' or exclude cases better suited for publish_job_verify, leaving the agent without decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only check but does not explicitly state side effects, return value, or error behavior. With no annotations, it fails to disclose whether the tool is pure, what it returns (e.g., boolean), or how edge cases (invalid timestamps, missing 'now') are handled.
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 a single, grammatically correct sentence with no wasted words. It front-loads the verb and clearly states the core functionality, achieving maximum conciseness for the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations, output schema, and parameter descriptions, the description should compensate by providing comprehensive context. It fails to explain the return value, the role of 'now', or any behavioral nuances, leaving significant gaps for a tool with only two parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions 'nextVerificationAt' but does not explain its format or semantics, and completely ignores the optional 'now' parameter. The agent receives no help understanding parameter meaning, especially since the schema provides no descriptions.
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 with a specific verb ('Check') and resource ('publish schedule'), and specifies the condition ('due for verification based on its nextVerificationAt'). This distinguishes it from sibling tools like publish_job_verify, which likely verifies job status rather than schedule due-ness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention workflow context, prerequisites, or any exclusions. Sibling tools exist but are not referenced, leaving the agent without decision criteria for tool selection.
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 carries the full burden. It discloses that the operation is idempotent and returns a durable job handle, which are useful behavioral traits. However, it does not explain side effects, prerequisites, or error conditions, leaving some ambiguity about the actual publish flow.
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 extremely concise, using two short sentences to convey the core purpose and key behavior. Every word earns its place, with no redundancy or irrelevant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, no output schema, no annotations), the description is insufficient. It fails to explain parameter usage, the expected return value beyond 'durable job handle', or any constraints on the input, leaving the agent with significant gaps in understanding how to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for its 8 parameters, and the description does not compensate. It only vaguely mentions 'final draft' without linking to specific parameters like draftId or markdown, providing no meaningful semantic guidance for the parameters.
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 a specific action: creating an idempotent publish job from a final draft. It distinguishes this from sibling tools like publish_job_run, publish_job_get, and publish_job_verify by focusing on creation and returning a durable handle.
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?
The phrase 'from a final draft' implies when this tool should be used, but there is no explicit guidance on alternatives or exclusions. Sibling tools are not referenced, and no conditions for choosing this over others are provided.
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 carries the transparency burden. It discloses a non-obvious behavioral trait ('without applying editorial preferences') and the verb 'Check' suggests a read-only operation. However, it does not state whether the tool mutates state, requires authentication, or how it reports incompleteness or rule violations.
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 a single, front-loaded sentence with no filler. Every word contributes to defining the tool's purpose and boundary, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given six parameters, three required fields, no annotations, and no output schema, the description is too sparse for an agent to fully understand invocation expectations. It does not mention return behavior, error conditions, or what 'completeness' concretely involves, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides no parameter-level details. It alludes to payload completeness and platform rules, but it does not explain the meaning or role of title, markdown, platform, tagIds, categoryId, or coverMediaId beyond what the raw schema already shows.
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 uses a specific verb ('Check') and names a concrete resource ('publish-payload completeness' plus 'verified official platform rules'). It also clarifies scope by explicitly excluding editorial preferences, distinguishing it from content-editing or publishing pipeline tools among the siblings.
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?
The description implies this is a preflight validation step ('Check publish-payload completeness and verified official platform rules') but gives no explicit when-to-use vs. alternatives, such as publish_liveness_check or publish_job_create. It does not name alternatives or exclusion criteria, leaving usage largely inferred from the tool name and sibling context.
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 convey behavioral traits itself. It clearly states the operation is a read and returns current status, implying no modification. However, it does not disclose details like error behavior, required authentication, or whether the job store is local-only, leaving some gaps.
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 a single, efficient sentence that is front-loaded with the verb and core concept. Every word adds value, with no fluff or repetition.
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?
For a simple read tool with one parameter and no output schema, the description covers the essential purpose but lacks richer context like error handling, prerequisites, or why the local store matters. It is adequate but not thorough, given no annotations or output schema to fill gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the 'jobId' parameter at all. Despite the parameter name being self-explanatory, the description fails to add any semantic meaning, such as format or required context, placing the full burden on 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 uses a specific verb 'read' to indicate retrieval, specifies the resource 'publish job', and adds scope 'one' and source 'local job store'. It clearly distinguishes from sibling tools like publish_job_create, publish_job_run, and publish_job_verify, 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implicitly clear: use this to read a publish job's status. However, it does not explicitly state when to prefer this over alternatives or mention any exclusions. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 discloses that the tool resolves a public URL, but does not indicate whether the operation is read-only, whether it blocks until verification completes, what permissions are required, or what error conditions might occur. This lack of behavioral detail is a significant gap.
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 a single, concise sentence that front-loads the primary action and result. It contains no redundant information or filler, making it efficient and easy to parse.
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?
For a tool with one parameter and no output schema, the description conveys the basic purpose and expected result. However, given the absence of annotations, it lacks important context about safety, retry behavior, and potential failure modes. The description is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter jobId has 0% schema description coverage. The description adds the hint that it refers to a 'previously submitted' job, which gives some semantic context. However, it does not explain how to obtain or format the ID, though the parameter name is self-explanatory.
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 action (verify), the resource (publish job), and the outcome (resolve its public URL). It is specific enough to distinguish from sibling tools like publish_job_get, which likely retrieves job details without providing the public URL.
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 phrase 'previously submitted publish job' provides clear context that this tool should be used after job submission, not for creating or running jobs. It does not explicitly mention alternatives or exclusions, but the context is reasonably clear for an agent to choose it over sibling tools.
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 carries the full burden. It adds the key behavioral disclosure that it does not return credentials, which is not inferable from the name alone. However, it does not specify return format, error behavior, or side effects, so it does not fully cover all transparency needs.
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 a single, focused sentence with no redundant words. It immediately states the action and the key limitation, earning every word.
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?
For a simple one-parameter tool, the description covers the core behavior but omits expected output details (e.g., boolean vs error) and any context about why one would probe auth. Since there is no output schema, the agent is left guessing about the return format, making this moderately complete but not fully sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 does not mention the 'platform' parameter or its possible values. While the schema provides an enum, the description adds no additional meaning about how to select or interpret the platform values, leaving the agent to infer from the tool name.
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 uses the specific verb 'Check' with a clear resource ('platform adapter') and outcome ('whether authenticated'). It also distinguishes itself from siblings by adding the safety constraint 'without returning credentials' and the focus on auth state, which is distinct from the publishing workflow tools.
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?
The description implies its use case (checking auth before publishing) but provides no explicit when-to-use vs alternatives or exclusions. Context signals show siblings, but the description does not reference them. For a simple one-parameter tool, the usage is fairly obvious, but the lack of explicit guidance keeps it at a minimum viable score.
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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