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save_conversation

Save complete conversation transcripts as persistent memory, auto-extracting project context and updating existing memories via append or replace modes.

Instructions

Save complete conversations as memory. REQUIRED: Send COMPLETE conversation in 'conversationContent' parameter (minimum 100 chars, should be thousands). Include EVERY message verbatim - NO summaries or partial content.

Intelligently tracks context, extracts project details, and routes to a single memory per conversation topic.

HOW SAVES TARGET MEMORIES:
- conversationId is auto-generated from title slug (e.g., "MCP Tools" → "mcp-tools")
- Same title (or explicit conversationId) → targets the existing memory
- The 'mode' parameter controls what happens to that existing memory:
  • mode='replace' (default): overwrites the existing content with what you send
  • mode='append': concatenates new content below existing with a timestamped separator
    (\n\n--- UPDATE <ISO8601> ---\n\n) — preserves all prior history in the live row
- The /save skill sets mode='append' automatically for living-document use
- For one-shot snapshots, ad-hoc captures, or explicit overwrite: pass mode='replace'

PRIOR CONTENT IS NEVER LOST:
- Even with mode='replace', prior content is snapshotted to memory_events audit log on every update
- Recovery from overwrites requires a one-off script (out-of-band)
- Use mode='append' if you want history to remain visible inline in the live memory

INTELLIGENT EXTRACTION (independent of mode):
- Auto-extracts project context (name, component, feature being discussed)
- Detects work iteration and status (planning/in_progress/completed/blocked)
- Generates smart titles like "Purmemo - Timeline View - Implementation"
- Tracks technologies, tools used, identifies relationships/dependencies

SERVER AUTO-CHUNKING:
- Large conversations (>15K chars) automatically split into linked chunks
- Small conversations (<15K chars) saved directly as single memory
- You always send complete content — server handles chunking
- APPEND + CHUNKING: append mode works only for content <15K chars. Saves >15K
  with mode='append' are rejected with a clear error — appending to chunked
  storage would double each chunk's content on re-save. For long-running living
  docs, send only the new delta since the last save (keep it <15K) or use
  mode='replace' for full re-saves.
- KNOWN CAVEAT: a doc that is saved small (single memory) and later grows past 15K
  transitions to chunked storage at a new conversation_id space — the original
  single memory becomes orphaned. Tracked under ADR-038 (uniform namespace).

EXAMPLES:
User: "Save progress" via /save skill
→ /save sets mode='append'; new content is appended below prior content

User: "Save this snapshot" (one-shot capture)
→ mode='replace' default; current content overwrites any existing memory at this title

User: "Save as conversation react-hooks-guide" with explicit append
→ save_conversation(conversationId="react-hooks-guide", mode="append")
→ Appends to existing memory at that ID (or creates if new)

WHAT TO INCLUDE (COMPLETE CONVERSATION REQUIRED):
- EVERY user message (verbatim, not paraphrased)
- EVERY assistant response (complete, not summarized)
- ALL code blocks with full syntax
- ALL artifacts with complete content (not just titles/descriptions)
- ALL file paths, URLs, and references mentioned
- ALL system messages and tool outputs
- EXACT conversation flow and context
- Minimum 500 characters expected - should be THOUSANDS of characters

FORMAT REQUIRED:
=== CONVERSATION START ===
[timestamp] USER: [complete user message 1]
[timestamp] ASSISTANT: [complete assistant response 1]
[timestamp] USER: [complete user message 2]
[timestamp] ASSISTANT: [complete assistant response 2]
... [continue for ALL exchanges]
=== ARTIFACTS ===
[Include ALL artifacts with full content]
=== CODE BLOCKS ===
[Include ALL code with syntax highlighting]
=== END ===

IMPORTANT: Do NOT send just "save this conversation" or summaries. If you send less than 500 chars, you're doing it wrong. Include the COMPLETE conversation with all details.

ARTIFACT PRESERVATION (ADR-025):
If this conversation produced artifacts (research reports, tables, frameworks, specs, design documents),
save them SEPARATELY using save_artifact after this call.
Flow: save_conversation first, then save_artifact for each artifact.
This ensures artifacts are preserved in full — do not try to embed large artifacts in conversationContent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoHow to handle a save that targets an existing memory (same title or conversationId). "replace" (default) overwrites the existing content with what you send. "append" concatenates new content below the existing content with a timestamped separator (\n\n--- UPDATE <ISO8601> ---\n\n). Use "append" for living documents you genuinely want to grow over time; use "replace" for one-shot snapshots and ad-hoc captures. The /save skill defaults to "append" automatically — you only need to pass this for explicit overrides.replace
tagsNoTags for categorization
titleNoTitle for this conversation memoryConversation 2026-09-18T23:50:55.920Z
priorityNoPriority level for this memorymedium
conversationIdNoOptional unique identifier for living document pattern. If provided and memory exists with this conversationId, UPDATES that memory instead of creating new one. Use for maintaining single memory per conversation that updates over time.
conversationContentYesCOMPLETE conversation transcript - minimum 500 characters expected. Include EVERYTHING discussed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv15.7.29
    • changedInput schema / properties / title / default
      Previous value: -"Conversation 2026-09-16T09:19:45.682Z"New value: +"Conversation 2026-09-18T23:50:55.920Z"
  2. Changed1 schema field changedv15.7.28
    • changedInput schema / properties / title / default
      Previous value: -"Conversation 2026-09-14T01:46:21.515Z"New value: +"Conversation 2026-09-16T09:19:45.682Z"
  3. Changed1 schema field changedv15.7.27
    • changedInput schema / properties / title / default
      Previous value: -"Conversation 2026-08-03T19:20:47.417Z"New value: +"Conversation 2026-09-14T01:46:21.515Z"
  4. Changed1 schema field changedv15.7.26
    • changedInput schema / properties / title / default
      Previous value: -"Conversation 2026-06-21T14:08:37.634Z"New value: +"Conversation 2026-08-03T19:20:47.417Z"
  5. First observedv15.7.23

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing auto-generated conversationId slugs, server-side chunking above 15K chars, rejection of append over 15K, audit snapshots in memory_events, and the ADR-038 orphaned-memory caveat. There is no contradiction with the annotations.

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 and somewhat repetitive, especially around sending complete content, but it is well organized with headers and bullets, and the critical constraints are front-loaded. Most sentences earn their place, though a few examples could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no output schema, it covers required content, failure cases, data-loss caveats, mode semantics, server behavior, and artifact preservation flow. An agent has sufficient context to invoke it correctly and avoid common mistakes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema already documents all 6 parameters with 100% coverage, the description adds substantial meaning: the required transcript format, minimum expected length, the exact timestamped separator for append mode, the behavior of explicit conversationId, and the append/chunking constraint.

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?

Opens with a specific verb and resource: 'Save complete conversations as memory.' It clearly differentiates from the save_artifact sibling by explicitly saying artifacts must be saved separately, so an agent can tell the two tools apart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use mode='replace' versus mode='append', explains that the /save skill automatically uses append, and gives a clear exclusion: artifacts should be saved with save_artifact after this call. This is strong when-to-use/alternative guidance.

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