Conducted MCP
Server Details
Stateless advisor + validator for Conducted Development: kickoff, artifact validation, rule checks.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.4/5 across 7 of 7 tools scored. Lowest: 3.7/5.
Each tool addresses a distinct methodology operation: decision logging, gate evaluation, kickoff planning, kickoff questions, procedure retrieval, standup due check, and artifact validation. No two tools share overlapping purposes.
All tool names use snake_case and are descriptive, but the pattern varies: some are verb_noun (evaluate_gate, validate_artifact), others are noun_noun or adjective_noun. Still readable and predictable overall.
Seven tools cover the main stages of the development methodology (kickoff, gates, decisions, standups, validation) without redundancy. The number feels well-scoped for the server's purpose.
The tool set covers key methodology workflows, but lacks a dedicated session management tool (opening/closing sessions) and only validates artifacts without providing update or creation tools. Minor gaps that agents can work around.
Available Tools
7 toolsdecision_log_guidanceJudge whether a situation belongs in the Decision LogAInspect
Encode the Decision-Log 'when to use it' rules. Set whichever apply: escalation_fired, gate_resolved_cross_cutting, affects_multiple_tickets, override_architectural, confined_to_one_session. Returns { should_log, reason, entry_template? }; when should_log is true the Context/Trigger/Decision/Rationale/Affects skeleton is returned. A decision confined to one session does not need an entry — the session notes suffice.
| Name | Required | Description | Default |
|---|---|---|---|
| escalation_fired | No | ||
| override_architectural | No | ||
| confined_to_one_session | No | ||
| affects_multiple_tickets | No | ||
| gate_resolved_cross_cutting | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the return structure ({ should_log, reason, entry_template? }) and the conditional return of a skeleton with Context/Trigger/Decision/Rationale/Affects when should_log is true. With no annotations, this provides solid behavioral insight, though it does not mention side effects or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the core purpose, and includes a list of parameters and output details without any fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description covers the main purpose, input criteria, and output structure. However, it lacks details on parameter interactions (e.g., if multiple flags can be true) and does not provide an example output format, leaving some incompleteness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and parameters have no descriptions. The description lists all five boolean flags and says 'Set whichever apply,' which adds some meaning by identifying the criteria. However, it does not explain each parameter's semantics or how they interact, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The title 'Judge whether a situation belongs in the Decision Log' and the description 'Encode the Decision-Log when-to-use-it rules' clearly state the tool's purpose. It uses specific verbs and resources, and it is easily distinguishable from sibling tools like evaluate_gate or kickoff_plan.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on when to use the tool (to encode decision-log rules) and includes an exclusion case: 'A decision confined to one session does not need an entry — the session notes suffice.' However, it does not explicitly compare to sibling tools or state when not to use it beyond the confined-session note.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
evaluate_gateEvaluate whether a goal brief's gates are resolvedAInspect
Encode the goal-brief rule that no session may begin while any gate is open. Supply either a structured gates list ([{ id, resolved }]) or a goal-brief content string, in which case the GATE LIST checkboxes (- [ ] / - [x]) are parsed. Returns { all_resolved, unresolved, may_begin } where may_begin === all_resolved. The server reads no files — the content is agent-supplied.
| Name | Required | Description | Default |
|---|---|---|---|
| gates | No | Structured gate list. | |
| content | No | A goal-brief markdown string whose GATE LIST is parsed. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the server reads no files and relies on agent-supplied content, and explains the return object format. Since no annotations exist, the description carries full burden and covers key behavioral aspects effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the core rule, then inputs and output. Every sentence is necessary and to the point, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple check tool with two parameters and no output schema, the description covers purpose, inputs, output, and a key behavioral trait. It is mostly complete, though missing guidance on mutual exclusivity of parameters and error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While the schema already describes the parameters with types, the description adds meaning by clarifying that gates is a structured list of objects with id and resolved, and content is parsed for markdown checkboxes. It also explains the optional nature and the parsing rule.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the rule 'no session may begin while any gate is open' and that the tool evaluates gate resolution from a structured list or markdown content. The verb 'encode' is slightly ambiguous but the overall purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that either a gates list or content string can be supplied, but it does not provide guidance on when to choose one over the other, nor does it compare to sibling tools or mention scenarios where this tool should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kickoff_planAssemble the kickoff file planAInspect
Assemble, from the bundled templates, the four _template.md copies (front-matter tokens replaced), decision-log.md, and a filled AGENT_CONVENTIONS.md (kickoff guide Steps 2–5). Supply project_type, the interview answers, optional detected (brownfield pre-fill fallback), and optional existing (the agent's inventory of files already present). Returns { files: [{ path, content, action }], missing, open_questions, warnings }. The plan is ready iff missing is empty (D5 strict); a file with any unresolved {{…}} token is reported in missing. Idempotent: already-present files are 'review'/'skip', never overwritten. The server returns content + paths only — it writes nothing (Model C, D2/D6).
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | Confirmed interview answers keyed by token id (e.g. PROJECT_NAME, LOCKED_DOCS). | |
| detected | No | Facts the agent detected by inspecting the repo (brownfield only). | |
| existing | No | Agent inventory of files already present in the target (for idempotent re-runs). | |
| project_type | Yes | 'greenfield' or 'brownfield'. |
Tool Definition Quality
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 idempotent behavior ('already-present files are review/skip, never overwritten') and that the server returns content only (writes nothing). These are key behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences front-load the main action, then detail inputs and return structure. Every sentence adds value without redundancy. Extremely concise for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully covers return structure (files, missing, open_questions, warnings), idempotency, and server behavior. All necessary context for correct invocation is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning: answers are 'keyed by token id', detected is 'brownfield only', existing is for 'idempotent re-runs'. This enriches the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'assemble' and specifies the exact resources: four template copies, decision-log.md, and AGENT_CONVENTIONS.md. It distinguishes from sibling tools like kickoff_questions and decision_log_guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains required and optional parameters and conditions for readiness (missing empty). It gives context for when to use optional fields like detected and existing, but doesn't explicitly list when not to use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kickoff_questionsGet the kickoff interview question setAInspect
Return the branched kickoff interview (DECISIONS.md D3/D4). Supply project_type: 'greenfield' asks the full set; 'brownfield' uses the agent-supplied detected facts (language, framework, tests, CI, existing docs) to pre-fill candidates and drop fully-inferable questions — except LOCKED_DOCS, which is always asked because it is human judgment. Returns { project_type, questions, inferred, notes }; the server reads no files.
| Name | Required | Description | Default |
|---|---|---|---|
| detected | No | Facts the agent detected by inspecting the repo (brownfield only). | |
| project_type | Yes | 'greenfield' or 'brownfield'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that server reads no files, pre-fills candidates from detected facts, drops inferable questions except LOCKED_DOCS, and returns structured object with project_type, questions, inferred, notes. No annotations exist, so description carries full burden and does so thoroughly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and front-loaded with main purpose. Each sentence adds value, but could be slightly more structured (e.g., bullet points for return object), but it's still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters (one nested) and no output schema, description fully explains behavior and return structure. Could mention if there are any limits or edge cases, but it's sufficient for its scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value by explaining how detected is used in brownfield (pre-fill, drop inferable) and that LOCKED_DOCS is always asked. This goes beyond the schema's basic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a branched kickoff interview for DECISIONS.md D3/D4, with specific behavior for greenfield vs brownfield. It distinguishes from siblings like kickoff_plan by focusing on question set retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear guidance on when to use greenfield vs brownfield based on project_type. Describes brownfield behavior using detected facts. However, does not explicitly mention when NOT to use this tool or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
next_procedureGet the procedure for a methodology phaseAInspect
Return the ordered procedure for where the agent is in the methodology loop. Supply phase (one of: kickoff, goal_brief, intent_doc, session_open, session_active, session_close, standup) and optional facts (e.g. a ticket id) to tailor the output. Returns { steps, reads_first, escalation_points, notes? } sourced from the bundled guides and conventions — the procedure half of advisor + validator. The server reads no files.
| Name | Required | Description | Default |
|---|---|---|---|
| facts | No | Optional facts to weave into the procedure (e.g. ticket id, work dir). | |
| phase | Yes | Which phase of the methodology loop the agent is in. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description explicitly states that the server reads no files, indicating a read-only operation. It also details the output structure and source (bundled guides and conventions), providing full transparency about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the main purpose. It efficiently includes essential details (phases, output fields, source) without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no output schema) and the context of sibling tools, the description adequately covers the purpose, parameters, output, and source. It provides enough information for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by listing the enum values for phase and giving an example for facts ('ticket id'), and explaining that facts tailor the output. This goes beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the ordered procedure for a methodology phase, lists the valid phases, and specifies the output fields. This distinguishes it from sibling tools like validate_artifact and evaluate_gate by focusing on procedural steps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (when the agent needs the ordered procedure for a phase) but does not explicitly exclude alternatives or mention when not to use it. The context is sufficient for an AI agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
standup_dueJudge whether a standup is dueAInspect
Given agent-supplied facts, decide whether a standup is due. Triggers in priority order: a deliverable gate reached → 'gate'; else a dependency intersection → 'intersection'; else more than five working days since the last standup → 'weekly'; else 'none'. Working days are an input (the working week varies by team), never computed from a calendar. Returns { due, reason, detail }.
| Name | Required | Description | Default |
|---|---|---|---|
| today | No | ||
| gate_reached | No | ||
| last_standup_date | No | ||
| dependency_intersection | No | ||
| working_days_since_last_standup | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Fully discloses the decision algorithm (priority order), input requirements (working days as input, not computed), and output structure ({ due, reason, detail }). No annotations needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise yet complete; three sentences clearly state purpose, logic, and return format. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers decision logic and output structure adequately for a tool with 5 parameters and no output schema. Could note expected date formats for 'today' and 'last_standup_date'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, description adds meaning by explaining how parameters (e.g., 'gate_reached', 'dependency_intersection') are used in the decision logic, though individual parameter details are not enumerated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: 'decide whether a standup is due'. It specifies the decision logic in priority order, making it distinct from sibling tools like 'evaluate_gate'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes when to use (given agent-supplied facts) and the conditions that trigger standup due. Does not explicitly contrast with siblings but provides clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_artifactValidate a methodology artifactAInspect
Strictly check whether a Conducted Development artifact's text satisfies the methodology's required structure. Supply the artifact's type and its full text (the server never reads files). Returns { valid, missing, warnings }: missing lists required sections that are absent, empty, or contain only unmodified template placeholder text (blocking); warnings lists sections that are present but look thin (advisory, non-blocking). valid is true iff missing is empty.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The full markdown text of the artifact to validate. | |
| artifact_type | Yes | Which artifact to validate. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses behavioral details: strict structural checking, required input (full text, not read from files), return format with fields and meaning (missing is blocking, warnings advisory, valid condition). This is thorough but could note that it does not modify data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct, starting with the core purpose, then defining inputs, and finally detailing the output format. Every sentence is informative and necessary, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and full schema coverage, the description provides sufficient context including return value semantics. It could additionally mention that validation is purely structural (not semantic), but overall completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by clarifying that the server does not read files and that content should be full markdown text. It also reinforces the parameter roles beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Strictly check') and the resource ('Conducted Development artifact's text'). It specifies the tool's distinct role from siblings like evaluate_gate or decision_log_guidance by focusing on structural validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when an artifact needs structural validation but does not explicitly state when to prefer this over alternatives or when not to use it. It provides no exclusions or context for sibling tools.
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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