kronos-forgemesh-mcp
OfficialServer Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct aspect of the Kronos market-intelligence domain: signals, risk, history, forecast, preflight checks, decision journaling, auditing, and whale flows. The only minor overlap is between risk and preflight (both mention cooldowns), but their purposes are clearly separated: one describes market risk state, the other is a pre-decision suitability check.
Naming Consistency5/5All tool names follow a consistent verb_kronos_noun pattern in snake_case (get_kronos_*, check_kronos_*, create_kronos_*, audit_kronos_*). The verb prefix clearly indicates the action, and the resource name is always kronos plus a specific suffix, making the set highly predictable.
Tool Count5/5With 8 tools, the server is well-scoped for a market-intelligence and decision-journaling service. Each tool covers a distinct need without redundancy or bloat, and the count comfortably fits within the ideal range.
Completeness4/5The server provides a solid coverage of the Kronos workflow: retrieving signals/risk/forecast, checking preconditions, creating auditable decisions, and auditing past decisions. A minor gap is the lack of a tool to fetch or list decision entries directly (only audit by decision_id), but this is workable and does not break the core workflow.
Average 3.9/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- Last stable release on
- 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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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?
With no annotations, the description carries the full burden. It discloses that the tool costs $0.15 USDC and creates an 'auditable' entry, which provides some behavioral context. However, it does not explain side effects, irreversibility, or what happens on success/failure, leaving a moderate transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. It front-loads the core purpose and adds the cost detail efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a cost and a unique creation purpose, the description does not explain what happens after creation, how to retrieve the entry, or why this tool should be preferred over others. The existence of 'audit_kronos_decision' as a sibling suggests a workflow, but the description is too terse to be fully complete for a paid, auditable action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description names extra fields (directional bias, calibrated confidence, decision_id) that are not part of the input schema, which only accepts 'symbol'. This creates confusion: an agent might think it can supply those fields, but the schema disallows them. The description fails to clarify the role of 'symbol' or how those other fields are determined, providing misleading guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('create') and resource ('Kronos market-intelligence journal entry'), clearly distinguishing this from sibling read/audit tools. The mention of directional bias, calibrated confidence, and decision_id further specifies the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (to create an auditable journal entry) and the sibling tools are read/audit operations, so the usage context is clear. However, it does not explicitly state when NOT to use this tool or name alternatives.
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?
The description discloses the cost ($0.05 USDC) and the categories of checks performed. With no annotations, this adds useful behavioral context, but it does not state whether the tool is read-only, how results are returned, or what happens if checks fail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one sentence that front-loads the action and lists the check categories, with the cost appended. No redundant phrases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It covers the what (market state, cooldowns, freshness, warnings) and the why (before creating a decision journal), plus cost. But it lacks details on output format, failure conditions, and how to interpret the results, which is significant given no output schema and no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention the 'symbol' parameter or how it influences the checks. The input schema provides an enum list, but with zero schema description coverage, the description should compensate but does not, leaving the agent to infer the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Check' and lists concrete resources (market state, cooldowns, freshness, warnings) and places it in the context of before creating a Kronos decision journal. This clearly distinguishes it from sibling getters and create/audit tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'before creating a Kronos decision journal,' providing clear timing for use. However, it does not mention alternatives or exclusions, such as what to use instead for real-time market data versus preflight checks.
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 behavioral disclosure burden. It discloses a cost ('Costs $0.05 USDC') and the historical scope ('up to 168 hours'), which is useful. However, it does not explicitly state that this is a read-only operation, or mention authentication or rate limits, so transparency is moderate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the main purpose and include an important cost detail. There is no redundant or vague wording, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given 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 covers the essentials: what it retrieves, the time window, the cost, and the intended use case. It could mention output format or any limitations beyond hours, but overall it is sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single parameter 'hours' with min, max, default, and description. The tool description adds no additional parameter semantics beyond reiterating 'up to 168 hours,' which is already present in the schema. Since schema description coverage is 100%, 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get up to 168 hours of timestamped Kronos signal history' using a specific verb ('Get') and resource ('Kronos signal history'). It also mentions 'for analysis and audit support,' which helps distinguish it from sibling tools like get_kronos_signals (likely current signals) and get_kronos_forecast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides contextual guidance ('for analysis and audit support') but does not explicitly state when to use this tool over siblings or when not to use it. There are no exclusions or alternative tool mentions, so the usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the cost ($0.02 USDC) and the read-only nature implied by 'Get'. However, it doesn't mention return format, pagination, or any rate limits. The cost disclosure adds value beyond the schema, but other behavioral details are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently conveys the tool's purpose and cost. There is no redundancy or unnecessary detail, making it well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with two parameters and no output schema. The description covers the core purpose, supported chains, and cost. It lacks details about the nature of the returned data or how the 'hours' parameter affects results, but the schema provides defaults and bounds. Given the low complexity, the description is minimally complete but could be enhanced with output expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explicitly lists the chains, covering the 'chain' parameter. However, the 'hours' parameter is entirely absent from the description, leaving its meaning and range to be inferred from the schema. The description adds some value for chain but fails to clarify the time window parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving whale, exchange, bridge, and stablecoin-flow context for specific chains. The verb 'Get' with the resource types and chain list is specific and distinguishes it from sibling tools like signals, risk, or history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on what data to expect (whale/exchange/bridge/stablecoin flows) and which chains are supported (Ethereum, Base, Arbitrum). While it doesn't explicitly mention when not to use it or alternatives, the distinct focus on flow context implies when it's appropriate relative to siblings.
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 adds the important cost of $0.07 USDC and implicitly suggests a read-only audit, but doesn't explicitly state side effects or safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose and followed by cost. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main flow and cost, but without an output schema it doesn't explain what 'outcome verdict' includes or how the window parameter affects results—leaving some ambiguity for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50%: decision_id has a clear origin description, and window is self-documenting via enum/default. The description text doesn't add parameter details, but the schema provides enough for both params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (audit a prior Kronos decision) and the purpose (compare against later prices to return an outcome verdict). This distinguishes it from sibling tools like creation or signal fetching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: when a prior decision_id exists and needs post-hoc evaluation. It provides clear context but doesn't explicitly mention alternatives or when not to use the tool.
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 discloses key behaviors: it returns a calibrated price range, current price, upside probability, and costs $0.05 USDC. This is more transparent than typical, though 'conformally calibrated' is jargon and side effects are not discussed; still, the operation is clearly read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the output components and followed by cost. Every word adds value; perfect conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description explicitly lists what is returned (range, price, probability). It also mentions cost, which is important for selection. For a simple single-parameter tool, this is fairly complete, though it does not cover error cases or edge conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (symbol) with an enum and default, but no description text (0% coverage). The description only says 'supported symbol', which adds little beyond the enum. Since the parameter is self-explanatory from its name and enum, the schema carries the meaning; the description does not compensate but also doesn't need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and precisely identifies the resource ('conformally calibrated 80% price range, current price, and upside probability') for a supported symbol. This clearly distinguishes it from sibling tools like signals, risk, history, or whale flows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining forecast metrics (price range and upside probability) and notes a cost, but does not explicitly state when to use this tool over alternatives or mention any exclusions. The context is clear but no alternatives are named.
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 behavioral traits. It adds the cost ($0.02 USDC) and indicates it returns current state and streaks, but does not mention whether it is read-only, response format, or any side effects. The cost disclosure is valuable, but other behavioral context is lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the core purpose and adds the cost as a key detail. Every word contributes, with no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool, the description provides a clear list of outputs (risk state, streaks, cooldown context) and notes the cost. It lacks details about the output shape or pagination, but given the simplicity, it is mostly sufficient. No output schema exists, so the description could slightly expand on what 'cooldown context' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool accepts zero parameters, so the description does not need to explain parameter meanings. The baseline for no parameters is 4, and the description confirms the lack of inputs implicitly by mentioning no arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Get') and resource ('Kronos market-risk state'), and also lists distinct outputs ('signal streaks', 'cooldown context'). This differentiates it from sibling tools like get_kronos_signals and get_kronos_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it is used for current risk-related data, but does not explicitly state when to use this tool over alternatives. No exclusions or alternative tool references are provided, leaving the agent to infer usage 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?
No annotations are provided, so the description carries the full burden. It discloses the $0.05 USDC cost, which is a key behavioral trait. However, it does not mention auth requirements, rate limits, or what the response structure looks like. For a read-only getter, this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no filler. It conveys the core function and cost efficiently, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description gives the essential details: what data is returned (signal context and ranked symbols) and for which assets. It could mention the return format or prerequisites like preflight checks, but the tool is simple enough that this is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific meaning, but none is needed. It clearly indicates the fixed scope (BTC, ETH, SOL, XRP, ADA).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and specific resource 'current Kronos signal context and ranked symbols' for five named assets. This distinguishes it from siblings like get_kronos_history and get_kronos_forecast by emphasizing 'current', and the asset list adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The use of 'current' implies this is for real-time snapshots rather than historical or forecast data, but there is no explicit guidance on when to choose this over sibling tools. No exclusions or alternative indications are provided.
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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