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4813ed753f
Ports functionality from 10+ separate plugins into ECC so users only need one plugin installed. Consolidates: pr-review-toolkit, feature-dev, commit-commands, hookify, code-simplifier, security-guidance, frontend-design, explanatory-output-style, and personal skills. New agents (8): code-architect, code-explorer, code-simplifier, comment-analyzer, conversation-analyzer, pr-test-analyzer, silent-failure-hunter, type-design-analyzer New commands (9): commit, commit-push-pr, clean-gone, review-pr, feature-dev, hookify, hookify-list, hookify-configure, hookify-help New skills (8): frontend-design, hookify-rules, github-ops, knowledge-ops, lead-intelligence, oura-health, pmx-guidelines, remotion Enhanced skills (8): article-writing, content-engine, market-research, investor-materials, investor-outreach, x-api, security-scan, autonomous-loops — merged with personal skill content New hook: security-reminder.py (pattern-based OWASP vulnerability warnings on file edits) Totals: 36 agents, 69 commands, 128 skills, 29 hook scripts
63 lines
3.9 KiB
Markdown
63 lines
3.9 KiB
Markdown
---
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name: knowledge-ops
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description: Evidence-first memory and context retrieval workflow for Hermes. Use when the user asks what Hermes remembers, points to OpenClaw or Hermes memory, or wants context recovered from a compacted session without re-reading already loaded files.
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origin: Hermes
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---
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# Knowledge Ops
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Use this when the user asks Hermes to remember something, recover an older conversation, pull context from a compacted session, or find information that "should be in memory somewhere."
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## Skill Stack
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Pull these companion skills into the workflow when relevant:
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- `continuous-learning-v2` for evidence-backed pattern capture and cross-session learning
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- `continuous-agent-loop` when the lookup spans multiple stores, compaction summaries, and follow-up recovery steps
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- `search-first` before inventing a new lookup path or assuming a store is empty
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- `eval-harness` mindset for exact source attribution and negative-search reporting
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## When To Use
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- user says `do you remember`, `it was in memory`, `it was in openclaw`, `find the old session`, or similar
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- the prompt contains a compaction summary or `[Files already read ... do NOT re-read these]`
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- the prompt says `use the context summary above`, `proceed`, or otherwise hands off loaded context plus a concrete writing, editing, or response task
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- the answer depends on Hermes workspace memory, Supermemory, session logs, or the historical knowledge base
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## Workflow
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1. Start from the evidence already in the prompt:
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- treat compaction summaries and `do NOT re-read` markers as usable context
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- if the prompt already says `use the context summary above` or asks you to proceed with writing, editing, or responding, continue from that loaded context first and search only the missing variables
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- do not waste turns re-reading the same files unless the summary is clearly insufficient
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2. Search in a fixed order before saying `not found`, unless the user already named the store:
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- `mcp_supermemory_recall` with a targeted query
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- grep `/Users/affoon/.hermes/workspace/memory/`
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- grep `/Users/affoon/.hermes/workspace/` more broadly
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- `session_search` for recent Hermes conversations
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- grep `/Users/affoon/GitHub/affaans_knowledge_base/` and `/Users/affoon/.hermes/openclaw-home/hub/workspace/memory/` for historical context
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3. If the user says the answer is in a specific memory store, pivot there immediately after the initial targeted recall:
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- `openclaw memory` means favor `/Users/affoon/GitHub/affaans_knowledge_base/` and `/Users/affoon/.hermes/openclaw-home/hub/workspace/memory/`
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- `not in this session` means stop digging through the current thread and move to persistent stores instead of re-reading current-session files
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4. Keep the search narrow and evidence-led:
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- reuse names, dates, channels, account names, or quoted phrases from the user
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- search the most likely store first instead of spraying generic queries everywhere
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5. Report findings with source evidence:
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- give the file path, session id, date, or memory store
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- distinguish between a direct hit, a likely match, and an inference
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6. If nothing turns up, say which sources were checked and what to try next. Do not say `not found` after a single failed search.
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## Pitfalls
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- do not ignore a compaction summary and start over from zero
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- do not keep re-reading files the prompt says are already loaded
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- do not turn a loaded-context handoff into a pure retrieval loop when the user already asked for an actual draft, edit, or response
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- do not keep searching the current session after the user already named OpenClaw or another persistent store as the likely source
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- do not answer from vague memory without a source path, date, or session reference
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- do not stop after one failed memory source when others remain
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## Verification
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- the response names the source store or file
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- the response separates direct evidence from inference
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- failed lookups list the sources checked, not just a bare `not found`
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