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Cross Session

mcp_m7_cross_session

Track coding session actions and validated feedback to build searchable project insights. Reuse that knowledge across sessions and format relevant context for AI prompts.

Instructions

M7 v3.0 Cross-Session Learning - Learn from session patterns across time.

Actions:

status

Check cross-session learning system status.

start

Start tracking a new session.

  • session_id: Session ID to track (required)

record

Record an action in current session.

  • action_data: { type, tool?, input, output, file?, success, userFeedback? }

get_context

Get full project learning context for AI prompts.

Search relevant knowledge.

  • query: Search query (required)

  • limit: Max results (default: 5)

validate

Validate an insight (user feedback).

  • insight_id: Insight ID (required)

  • valid: true/false (required)

ci_result

Record CI/CD result for insight validation.

  • ci_result: { type, success, details?, affectedInsights? }

stats

Get learning statistics.

cleanup

Cleanup old/low-confidence data.

  • cleanup_options: { olderThanDays?, belowConfidence? }

format_prompt

Format context for injection into AI prompt.

  • query: Optional query for relevant knowledge

Input Schema

NameRequiredDescriptionDefault
limitNoMax results (default: 5)
queryNoSearch query
validNoValidation result
actionYes
ci_resultNo
insight_idNoInsight ID for validation
session_idNoSession ID for start action
action_dataNo
cleanup_optionsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.18.1

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It does not disclose whether actions like 'record', 'validate', or 'cleanup' mutate persisted data, whether cleanup is destructive or reversible, whether sessions persist across calls, or what permissions are required. The action names hint at behavior but the description adds no explicit behavioral context.

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 long but well-structured with headings and bullet lines per action, and the purpose is front-loaded. Every action line maps to a real enum value, so the length is largely earned, though the catalog format could be slightly tighter.

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?

For an 11-action multiplexed tool with 9 parameters, nested objects, no output schema, and no annotations, the description is incomplete. It does not explain return values, persistence semantics, side effects of write actions, cleanup safety, or how action selection interacts with sibling tools, leaving material gaps for an agent to call 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?

Despite only 56% schema description coverage, the description documents per-action parameter requirements and nested shapes: action_data fields {type, tool?, input, output, file?, success, userFeedback?}, ci_result fields {type, success, details?, affectedInsights?}, and cleanup_options fields {olderThanDays?, belowConfidence?}. It also marks required parameters for start, search, and validate, adding clear value beyond the schema's top-level property descriptions.

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 states the tool is for cross-session learning across time and enumerates all 11 actions with one-line summaries, making the resource and capabilities clear. It does not explicitly differentiate itself from siblings such as mcp_m7_session or mcp_m7_memory, so it stops short of a 5.

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?

Each action line implies when that action is used (e.g., 'start tracking a new session', 'record an action in current session'), but there is no explicit guidance on when to choose this tool over sibling tools like mcp_m7_session, mcp_m7_memory, or mcp_m7_validate. The action catalog is helpful but leaves alternative selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.