tools/sage-claude-plugin/skills/continue/SKILL.md
Session resumption with context
npx skillsauth add xoai/sage continueInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Resume any active cycle with full context. The user doesn't need to remember which workflow or initiative was in progress.
Scan .sage/work/*/manifest.md for cycles where
status: in-progress or status: paused.
Sage: Resuming [{title}] — {workflow}, phase: {phase}.
{context summary, verbatim from manifest}
Next step: {next step from manifest}
[C] Continue — pick up where we left off
[S] Status — show me full cycle state before continuing
[X] Different — I want to work on something else
Pick C/S/X, or tell me what you need.
On [C]: Load manifest context. Route to the workflow's Auto-Pickup with manifest as primary context source. The resuming agent follows the handoff guidance and does NOT re-ask questions already resolved.
On [S]: Show full manifest contents (State, Context summary, Decisions, Open questions, Handoff guidance). Then offer [C]/[X].
On [X]: "Describe what you want to work on, or type / to see commands."
Sage: Found {N} active cycles:
[1] {title A} — {workflow}, phase: {phase} (updated: {date})
[2] {title B} — {workflow}, phase: {phase} (updated: {date})
[3] Start something new
Pick 1-{N+1}, type / for commands, or describe what you need.
On selection: load that cycle's manifest, route to its workflow.
Sage: No active cycles found.
Describe what you want to work on, or type / to see commands.
The resuming agent behaves as if it has the context described in the manifest's context summary. It follows the handoff guidance. It does NOT re-ask questions the previous agent already resolved — those decisions are in the manifest and decisions.md.
/continue reads the workflow field in the manifest and activates
the corresponding workflow's Auto-Pickup:
| workflow field | Routes to | |---------------|-----------| | build | /build Auto-Pickup | | architect | /architect Auto-Pickup | | fix | /fix Auto-Pickup | | research | /research Auto-Pickup | | design | /design Auto-Pickup | | analyze | /analyze Auto-Pickup | | reflect | /reflect Auto-Pickup |
tools
Captures agent mistakes, corrections, and discovered gotchas so they are not repeated. Use when: (1) a command or operation fails unexpectedly, (2) the user corrects the agent, (3) the agent discovers non-obvious behavior through debugging, (4) an API or tool behaves differently than expected, (5) a better approach is found for a recurring task. Also searches past learnings before starting tasks to avoid known pitfalls. Activate alongside the sage-memory skill — they share the same MCP backend but serve different purposes (sage-memory = codebase knowledge, sage-self-learning = agent mistakes and gotchas).
development
Typed knowledge graph stored in sage-memory. Use when creating or querying structured entities (Person, Project, Task, Event, Document), linking related objects, checking dependencies, planning multi-step actions as graph transformations, or when skills need to share structured state. Trigger on "remember that X is Y", "what do I know about", "link X to Y", "show dependencies", "what blocks X", entity CRUD, cross-skill data access, or any request involving structured relationships between things.
tools
Integrates sage-memory into Sage workflows. Teaches the agent when to remember (store findings during work), when to recall (search memory at session start and task start), and how to learn (structured knowledge capture via sage learn). Use when the user mentions memory, remember, recall, learn, capture knowledge, onboard to codebase, or when starting any session where sage-memory MCP tools are available.
tools
Captures agent mistakes, corrections, and discovered gotchas so they are not repeated. Use when: (1) a command or operation fails unexpectedly, (2) the user corrects the agent, (3) the agent discovers non-obvious behavior through debugging, (4) an API or tool behaves differently than expected, (5) a better approach is found for a recurring task. Also searches past learnings before starting tasks to avoid known pitfalls. Activate alongside the sage-memory skill — they share the same MCP backend but serve different purposes (sage-memory = codebase knowledge, sage-self-learning = agent mistakes and gotchas).