autoresearch-loop
Domain-agnostic metric-driven improvement loop, generalizing Karpathy's autoresearch. Use when you want an agent to discover what…
Recover missing conversation context after explicit compaction or truncation, or when the user explicitly asks to recover prior work. Use for requests such as "where were we before compaction?" when the current thread is insufficient. Do not trigger on a generic "continue" when
$ npx -y skills add jdrhyne/agent-skills --skill context-recovery --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/context-recoveryContext preview
The summary Claude sees to decide when to auto-load this skill.
Recover missing conversation context after explicit compaction or truncation, or when the user explicitly asks to recover prior work. Use for requests such as "where were we before compaction?" when the current thread is insufficient. Do not trigger on a generic "continue" when
name: context-recovery
description: Recover missing conversation context after explicit compaction or truncation, or when the user explicitly asks to recover prior work. Use for requests such as "where were we before compaction?" when the current thread is insufficient. Do not trigger on a generic "continue" when the current thread already provides an actionable next step.
metadata:
{
"openclaw":
{
"emoji": "🔄",
"repository": "https://github.com/jdrhyne/agent-skills/tree/main/skills/context-recovery",
},
}Recover the smallest amount of conversation history needed to resume work safely. Default to the current thread and make uncertainty visible.
Activate when both of these are true:
1. There is recovery intent or evidence: an explicit compaction/truncation marker, or the user asks to recover, recall, reconstruct, or locate prior conversation context. 2. The current thread does not already contain enough reliable state to perform the requested next action.
Do **not** activate merely because the user says "continue," "go on," or "next" when the current thread contains an actionable task or promised next step. Continue that work normally. Likewise, a vague reference such as "the project" is not proof that context was lost; ask one focused clarification when the intended object cannot be identified from the current thread.
If compaction is evident but a supplied summary already contains sufficient state, use that current context and label any uncertainty. Do not retrieve more history automatically.
Use the first sufficient stage and stop.
Inspect the active turn, runtime-provided compaction summary, current thread metadata, and already supplied messages. This is the default and needs no additional approval.
If available, use the runtime's authenticated current-session or current-thread history capability. Inspect the live capability schema rather than assuming a connector name or parameter shape. Start with the most recent relevant messages and impose a hard bound of 50 items or 24 hours, whichever is smaller. Narrow further when a task, timestamp, or identifier is known.
Current-thread recovery does not require an extra approval because it remains inside the conversation the user is actively using. State the retrieved item count and time range.
Another channel, thread, session, workspace, memory store, local transcript, or log is a separate source. Before accessing it, show:
Then obtain explicit user approval. An instruction to recover a named external source identifies the desired scope but does not waive this action-time approval. Do not retrieve anything from that source before approval, and do not broaden an approved scope without a new approval.
Never discover context by globbing or recursively searching session, archive, home, project, or memory directories. Prefer the runtime's current authenticated session/thread APIs. If no suitable scoped capability exists, explain the limitation and ask the user for a specific source or a pasted excerpt.
Suggested approval prompt:
> The current thread does not resolve `<missing fact>`. I can search `<source>` from `<time range>`, up to `<limit>` items; this may expose `<privacy category>`. Should I perform that read-only recovery?
For each recovered fact, preserve:
Keep a bounded evidence timeline. Seek counterevidence for status claims such as completed, approved, pushed, published, or deployed. Tool output or a later verified state can support those claims; an assistant's earlier promise cannot.
When sources disagree, surface the conflict instead of choosing silently. A later item may supersede an earlier one only when it explicitly records the change or independent evidence verifies the later state. Otherwise present both versions, their timestamps and sources, and the decision still needed.
Do not claim that recovery is complete when a source is partial, unavailable, redacted, or outside the approved scope.
Return a compact recovery report:
## Recovered context - Scope: <current supplied context/current thread/approved source> - Sources: <source IDs, time ranges, and item counts> - Likely active task: <task or unknown> (<confidence and reason>) ### Evidence timeline - <timestamp> — <source and speaker> — <fact or claim> ### Conflicts and counterevidence - <claim A versus claim B, or "None found within the approved scope"> ### Unresolved - <missing or ambiguous facts> ### Proposed next step - <one safe action; do not imply authorization for a write>
If recovery does not identify the task reliably, say so and ask one focused question. Do not fabricate contin
A collection of AI agent skills and prompts for OpenClaw (formerly Clawdbot), Claude Code, Codex, and other LLM-based coding assistants. 🤝 Contributions Welcome! Have a skill that makes your AI agent smarter? We'd love to include it.
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