personal-brand-mcp

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation5/5
Each tool targets a distinct aspect of personal branding: positioning, bio auditing, bio rules, content pillars, platform strategy, growth signals, and a full pack. The only closely related tools are audit_bio and get_bio_rules, but their roles are clearly separated (applying rules vs. providing them), so there is no ambiguity.
Naming Consistency4/5
All tool names use lowercase with underscores and generally follow a verb_noun pattern, but the verbs vary: most use 'get_', while audit_bio and interpret_growth_signal use different verbs. This is readable and predictable, though a more uniform verb choice would improve consistency.
Tool Count5/5
Seven tools is well within the ideal range for a domain-specific server. Each tool covers a major component of personal branding (positioning, bio, content, platform, signals), and none feel redundant or unnecessary.
Completeness5/5
The toolset covers the full personal-brand workflow: strategic positioning, bio rules with an audit action, content pillars, platform strategy, growth signal interpretation, and a full-pack convenience. There are no obvious missing operations for the server's declared purpose.
Average 3.8/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of transparency. It describes the content returned (platform roles, conversion path, cadence floor, watch-out) without noting whether the operation is read-only, has side effects, or requires specific permissions. Since the tool name suggests a read-only query, some transparency is implied, but explicit disclosure is missing.
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 a single sentence, but it is dense and packs multiple pieces of information using parenthetical shorthand. It is concise and front-loaded with the core purpose, though the format might be slightly compressed for readability. It earns its place without unnecessary fluff.
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?
Given the simplicity (one optional parameter, no output schema), the description provides the essence of what the tool returns. However, it does not clarify whether the tool returns all platforms at once or a single platform when the parameter is provided, nor does it explain the returned format or the meaning of 'watch-out'. It is adequate but leaves some ambiguity.
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 input schema already defines the optional 'platform' parameter with an enum of six values. The description adds significant semantic value by explicitly mapping each platform to its strategic role (tiktok=reach, instagram=trust, etc.), which helps the agent understand the meaning of each enum option beyond the schema's generic 'Optional: one platform'.
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 identifies the tool's output: the strategic role of each platform, including specific attributes like conversion path, cadence floor, and watch-out. Although it lacks an explicit verb like 'retrieve' or 'get', the tool's name and the descriptive content make the purpose clear. It is differentiated from siblings like get_positioning_framework and get_content_pillars.
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?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites or exclusions. Sibling tools such as get_positioning_framework and get_content_pillars are conceptually distinct, but the description does not explain scenarios favoring this tool over those.
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 must convey behavioral traits. However, it only summarizes the framework content and does not disclose whether the tool is read-only, has side effects, or requires any prerequisites. It does not contradict annotations (since there are none), but it fails to provide meaningful behavioral transparency.
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 sentences long, with no wasted words. The first sentence enumerates the framework's components compactly, and the second provides a strategic context. It is well-structured and easy to parse.
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 simplicity (zero parameters, no output schema), the description provides a thorough overview of the framework's contents, which is helpful for understanding what to expect. It does not explicitly state the return format, but for a content-delivery tool this is not a critical omission. The description is complete enough for the tool's complexity.
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 tool has zero parameters, so there is no parameter documentation burden. The baseline for 0-parameter tools is 4, and the description adds context about the output content, which is sufficient. No parameter semantics are needed.
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 identifies the resource: the positioning framework, listing its key components (WHO x OUTCOME x HOW x RECEIPT, four checks, anti-patterns, proof-inventory, moat check). While it lacks an explicit verb like 'retrieves' or 'returns,' the tool name plus the content summary make the purpose unambiguous. It distinguishes from sibling tools by focusing specifically on positioning.
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 statement 'Positioning is upstream of every other brand decision' implies that this tool should be used early, before other brand-related tools, but it does not explicitly name alternatives or define when not to use it. This gives a clear contextual hint but lacks concrete usage boundaries.
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?
There are no annotations, so the description must fully disclose behavior. It does not explicitly state that this is a read-only operation or mention any side effects, permissions, or return format. The description only covers content, not behavioral traits such as safety, rate limits, or error handling. The tool name implies a 'get' operation, but the description itself does not confirm read-only behavior.
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 two concise sentences, with the first sentence conveying the core purpose and the second listing platforms. It is front-loaded and wastes no words. The platform list is slightly redundant with the schema enum, but it still serves as a quick reference. Overall, it is appropriately sized and easy to scan.
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 simplicity of the tool (one parameter, no output schema), the description provides a reasonable summary of what the tool returns: 'what the first line must do, character priorities, CTA shape.' This covers the essential return content. It does not provide concrete examples or detailed structure, but for a straightforward lookup tool, the level of detail is adequate. The lack of an output schema is offset by this description.
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?
Schema coverage is 0%, so the description must compensate for the parameter documentation. It mentions 'per platform' and lists the valid platform values, which aligns with the enum in the schema. However, it does not add significant meaning beyond the enum itself—the value of the parameter is mostly self-evident from the tool name and the schema. The description adds some context but not enough to fully compensate for the lack of a schema description.
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 function: providing bio architecture per platform. It specifies the key aspects ('what the first line must do, character priorities, CTA shape'), which distinguishes it from siblings like audit_bio (which evaluates existing bios) and get_platform_strategy (which is broader). The resource is clearly 'bio rules' with a per-platform scope.
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 clearly indicates the context: use when you need platform-specific bio rules. The inclusion of the platform list (tiktok, instagram, linkedin, x, youtube) clarifies the intended scope. However, it does not explicitly mention alternatives or when not to use this tool, missing a stronger differentiation from sibling tools like audit_bio.
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?
No annotations are present, so the description carries the full burden. It discloses what the tool provides: pillar breakdown, percentages, failure modes, and portfolio rules. This is reasonably transparent for a read-only informational tool, though it does not explicitly state the absence of side effects.
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, dense sentence that front-loads the core concept ('4-pillar content system') and packs in percentages, component details, and failure modes without wasted words.
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 lacking an output schema, the description adequately outlines the expected response content: pillars, percentages, what each does, failure mode, and portfolio rules. It is complete for a no-parameter reference tool, though it omits any relationship to sibling tools or use cases.
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 tool has zero parameters, so the baseline is 4 per the rubric. There is no parameter information needed, and the schema trivially covers everything.
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 identifies the tool's subject: the 4-pillar content system with specific percentages and components. It distinguishes itself from sibling tools like get_positioning_framework or get_platform_strategy by naming a distinct 'content system' resource, though it lacks an explicit verb like 'returns'.
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 about when to use this tool versus siblings such as get_positioning_framework or get_full_pack. The description only states what the content is, not the scenarios in which it should be selected.
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?
Without annotations, the description carries the burden. It discloses that the response is a single payload containing multiple specified components, which is useful. However, it does not mention read-only nature, whether it aggregates from other tools, or any performance implications, leaving some ambiguity.
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 one concise sentence with a clear primary clause followed by a list of contents. Every word adds value, and the structure front-loads the main idea 'complete personal-brand library in one payload'.
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 simplicity (no params, no annotations, no output schema), the description lists the contained components but does not provide an example structure or explicitly state that it aggregates the sibling tools. It is adequate for the complexity but could be more explicit about the return format.
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?
There are no parameters to document, and the schema is empty. The description has nothing to add regarding parameters, so per the rubric, a baseline of 4 is appropriate.
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 identifies the tool as providing the complete personal-brand library in a single payload, listing the components (positioning, bio rules, pillars, platform strategy, signal reads). This distinguishes it from sibling tools that focus on individual aspects, though it lacks an explicit action verb.
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 is when a user wants all components combined, but it does not explicitly state when to use this tool versus the individual sibling tools, nor does it mention exclusions. The 'complete' and 'one payload' phrasing provides some context but leaves the decision to the agent.
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 clearly discloses what the tool does (checks specific bio issues), the platform scope, and the return format (PASS/NEEDS WORK with a rewrite recipe). This is transparent for a read-only audit tool, though it does not discuss edge cases like missing platform.
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 sentences, front-loaded with the core action and resource. Every sentence contributes specific value: the first lists audit dimensions, the second lists platforms and the return format. No repetition or 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?
For a 2-parameter tool with no output schema, the description covers the key aspects: input (bio), optional platform (and its values), the audit criteria, and the output (PASS/NEEDS WORK with rewrite recipe). It does not explain default platform behavior, but this is a minor gap. Sibling tools are related but not referenced; that is acceptable here.
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?
Schema coverage is 0%, so the description must compensate. It adds meaning by indicating that 'platform' is used for per-platform character limits and listing valid values, and 'bio' is unambiguously the subject. However, it does not clarify behavior when platform is omitted (e.g., defaults to all platforms) or impose input constraints beyond being a string.
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 ('Audit') and resource ('profile bio'), and enumerates the exact audit dimensions (character limits, hype titles vs receipts, title-first openers, outcome language). This clearly distinguishes it from sibling tools like get_bio_rules or get_platform_strategy, which focus on rules and strategy rather than auditing.
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 through the action 'Audit', but does not explicitly state when to use this tool versus siblings or provide exclusions. It lists platforms and audit areas, yet offers no comparative guidance such as 'use get_bio_rules for rule reference' or 'when a bio needs a quick review'.
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 provided, the description carries the full burden. It explicitly states the behavior: interpreting a growth signal and returning its meaning plus the fix order. This gives the agent a clear picture of what to expect, though edge cases or side effects are not mentioned (though likely none exist).
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?
A single sentence packs all essential information: the tool's function, the specific input values, and the output type. No redundant words or repetition of schema elements.
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?
The tool is simple (one parameter, no output schema, no annotations). The description covers the input domain and the returned content. It lacks explicit details about response format, but for this use case the provided information is sufficient for an agent to invoke it correctly.
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 the description must compensate. It lists the enum values and explains that they represent growth patterns, adding context beyond the bare schema. It does not explain each pattern in detail, but the self-descriptive enum names make this sufficient.
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 identifies the tool as interpreting growth patterns, enumerates the specific signal values it handles, and states the output (meaning and fix order). This distinguishes it from sibling tools which focus on positioning, bio, or strategy.
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 implies the tool should be used when a user has one of the listed growth signals. However, it does not explicitly state when not to use it or contrast it with alternative tools. The context is clear but exclusions are absent.
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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