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by njlnaet

Log Session Note

coderswap_log_session_note

Record session summaries to maintain continuity across research projects by capturing key insights and progress markers for future reference.

Instructions

Record lightweight ingestion summary for session continuity (non-DSL)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
summary_textYes
job_idNo
ingestion_metricsNo
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYes
timestampYes
project_idYes

Implementation Reference

  • The asynchronous handler function that executes the core logic of the 'coderswap_log_session_note' tool. It checks for guardrail bypasses, generates a note ID, logs the session note details using the log utility, and returns structured output with success or error response.
    async ({ project_id, summary_text, job_id, ingestion_metrics, tags }) => {
      if (containsGuardrailBypass({ project_id, summary_text, job_id, ingestion_metrics, tags })) {
        return guardrailViolationResponse()
      }
      try {
        log('debug', 'Logging session note', { project_id, job_id })
    
        // Generate a simple note ID
        const timestamp = new Date().toISOString()
        const note_id = `note_${Date.now()}`
    
        // Log the note (for now, just to console/debug)
        log('info', `Session note logged for project ${project_id}`, {
          note_id,
          summary_text,
          job_id,
          ingestion_metrics,
          tags
        })
    
        const output = {
          note_id,
          project_id,
          timestamp
        }
    
        return {
          content: [{
            type: 'text',
            text: `✓ Logged session note: ${summary_text.substring(0, 100)}${summary_text.length > 100 ? '...' : ''}`
          }],
          structuredContent: output
        }
      } catch (error) {
        log('error', 'Failed to log session note', { project_id, error: error instanceof Error ? error.message : error })
        return {
          content: [{
            type: 'text',
            text: `✗ Failed to log session note: ${error instanceof Error ? error.message : 'Unknown error'}`
          }],
          isError: true
        }
      }
    }
  • The inputSchema and outputSchema definitions using Zod for validating the tool's inputs (project_id, summary_text, etc.) and outputs (note_id, etc.). Includes title and description.
    {
      title: 'Log Session Note',
      description: 'Record lightweight ingestion summary for session continuity (non-DSL)',
      inputSchema: {
        project_id: z.string().min(1, 'project_id is required'),
        summary_text: z.string().min(1, 'summary_text is required'),
        job_id: z.string().optional(),
        ingestion_metrics: z.any().optional(),
        tags: z.any().optional()
      },
      outputSchema: {
        note_id: z.string(),
        project_id: z.string(),
        timestamp: z.string()
      }
  • src/index.ts:634-696 (registration)
    The server.registerTool call that registers the 'coderswap_log_session_note' tool with the MCP server, providing the tool name, metadata/schemas, and handler function.
    server.registerTool(
      'coderswap_log_session_note',
      {
        title: 'Log Session Note',
        description: 'Record lightweight ingestion summary for session continuity (non-DSL)',
        inputSchema: {
          project_id: z.string().min(1, 'project_id is required'),
          summary_text: z.string().min(1, 'summary_text is required'),
          job_id: z.string().optional(),
          ingestion_metrics: z.any().optional(),
          tags: z.any().optional()
        },
        outputSchema: {
          note_id: z.string(),
          project_id: z.string(),
          timestamp: z.string()
        }
      },
      async ({ project_id, summary_text, job_id, ingestion_metrics, tags }) => {
        if (containsGuardrailBypass({ project_id, summary_text, job_id, ingestion_metrics, tags })) {
          return guardrailViolationResponse()
        }
        try {
          log('debug', 'Logging session note', { project_id, job_id })
    
          // Generate a simple note ID
          const timestamp = new Date().toISOString()
          const note_id = `note_${Date.now()}`
    
          // Log the note (for now, just to console/debug)
          log('info', `Session note logged for project ${project_id}`, {
            note_id,
            summary_text,
            job_id,
            ingestion_metrics,
            tags
          })
    
          const output = {
            note_id,
            project_id,
            timestamp
          }
    
          return {
            content: [{
              type: 'text',
              text: `✓ Logged session note: ${summary_text.substring(0, 100)}${summary_text.length > 100 ? '...' : ''}`
            }],
            structuredContent: output
          }
        } catch (error) {
          log('error', 'Failed to log session note', { project_id, error: error instanceof Error ? error.message : error })
          return {
            content: [{
              type: 'text',
              text: `✗ Failed to log session note: ${error instanceof Error ? error.message : 'Unknown error'}`
            }],
            isError: true
          }
        }
      }
    )
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states it 'records' a summary, implying a write operation. It doesn't disclose behavioral traits like permissions needed, idempotency, rate limits, or what 'session continuity' entails operationally, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded in a single sentence, with no wasted words. However, it could be more structured by explicitly separating purpose from constraints or usage notes.

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 5 parameters with 0% schema coverage and no annotations, the description is incomplete—it doesn't explain parameters or behavioral details. The presence of an output schema mitigates this slightly, but overall, it's inadequate for a tool with multiple undocumented inputs.

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 but adds no parameter-specific information. It doesn't explain what 'project_id', 'summary_text', 'job_id', 'ingestion_metrics', or 'tags' mean or how they relate to the tool's purpose, failing to address the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Record') and resource ('lightweight ingestion summary for session continuity'), specifying it's for 'non-DSL' contexts. However, it doesn't explicitly differentiate from sibling tools like 'coderswap_research_ingest' or 'coderswap_validate_search', which might involve similar concepts.

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 minimal guidance by mentioning 'session continuity' and 'non-DSL', but lacks explicit when-to-use rules, prerequisites, or alternatives compared to siblings. No clear context for choosing this over other tools is given.

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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