eve-agent-memory
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
What this skill does
# Eve Agent Memory
Agents on Eve Horizon have no built-in "memory" primitive, but the platform provides storage systems at every timescale. This skill teaches how to compose them into coherent memory for agents that learn, remember, and share.
## The Memory Problem
Every agent starts cold. Without deliberate memory design, agents:
- Re-discover the same facts on every job.
- Lose context when jobs end.
- Cannot share learned knowledge with sibling agents.
- Accumulate stale information with no expiry.
Solve this by mapping **what to remember** to **where to store it**, using the right primitive for each timescale.
## Storage Primitives by Timescale
### Short-Term (within a job)
**Workspace files** — the git repo checkout available during job execution.
```bash
# Workspace is at $EVE_REPO_PATH
# Write working state to .eve/ (gitignored by convention)
echo '{"findings": [...]}' > .eve/agent-scratch.json
# Workspace modes control sharing:
# job — fresh checkout per job (default)
# session — shared across jobs in a session
# isolated — no git state, pure scratch
eve job create --workspace-mode session --workspace-key "auth-sprint"
```
Use for: scratch notes, intermediate results, coordination inbox files. Ephemeral by design — workspace state does not survive the job unless committed to git or saved elsewhere.
**Coordination inbox** — `.eve/coordination-inbox.md` is auto-generated from coordination thread messages at job start. Read it for sibling status without API calls.
**Agent KV Store** — lightweight operational state with optional TTL. Use for: feature flags, rate counters, agent state machines, deduplication keys. Namespace-partitioned.
```bash
# Set a KV value with TTL
eve kv set --org $ORG_ID --agent $AGENT_SLUG --key "pr-123-status" --value '{"phase":"review"}' --namespace workflow --ttl 86400
# Get a KV value
eve kv get --org $ORG_ID --agent $AGENT_SLUG --key "pr-123-status" --namespace workflow
# List keys in a namespace
eve kv list --org $ORG_ID --agent $AGENT_SLUG --namespace workflow
# Batch get multiple keys
eve kv mget --org $ORG_ID --agent $AGENT_SLUG --keys "pr-123-status,pr-456-status" --namespace workflow
# Delete a key
eve kv delete --org $ORG_ID --agent $AGENT_SLUG --key "pr-123-status" --namespace workflow
```
### Medium-Term (across jobs within a project)
**Job attachments** — named key-value pairs attached to any job. Survive after job completion.
```bash
# Store findings
eve job attach $EVE_JOB_ID --name findings.json --content '{"patterns": [...]}'
eve job attach $EVE_JOB_ID --name summary.md --file ./analysis-summary.md
# Retrieve from any job (including parent/child)
eve job attachment $PARENT_JOB_ID findings.json --out ./prior-findings.json
eve job attachments $JOB_ID # list all
```
Use for: job outputs, decision records, analysis results. Attached to a specific job, so retrievable by job ID. Good for passing structured data between parent and child jobs.
**Threads** — message sequences with continuity across sessions.
```bash
# Project threads maintain chat context
eve thread messages $THREAD_ID --since 1h
# Coordination threads connect parent/child agents
eve thread post $COORD_THREAD_ID --body '{"kind":"update","body":"Found 3 auth issues"}'
eve thread follow $COORD_THREAD_ID # poll for sibling updates
```
Use for: inter-agent communication, rolling context, coordination. Thread summaries provide compressed history. Coordination threads (`coord:job:{parent_job_id}`) are auto-created for team dispatches.
**Thread Distillation** — convert thread conversations into memory docs or org docs. Use for: preserving valuable discussion outcomes as searchable knowledge.
```bash
eve thread distill $THREAD_ID --org $ORG_ID --agent reviewer --category learnings --key "auth-discussion-findings"
```
**Resource refs** — versioned pointers to org documents, mounted into job workspaces.
```bash
eve job create \
--description "Review the approved plan" \
--resource-refs='[{"uri":"org_docs:/pm/features/FEAT-123.md@v3","label":"Plan","mount_path":"pm/plan.md"}]'
```
Use for: pinning specific document versions as job inputs. The referenced document is hydrated into the workspace at the specified mount path. Events track hydration success/failure.
### Long-Term (across projects, persistent)
**Org Document Store** — versioned documents scoped to the organization.
```bash
# Store knowledge
eve docs write --org $ORG_ID --path /agents/learnings/auth-patterns.md --file ./auth-patterns.md
# Retrieve
eve docs read --org $ORG_ID --path /agents/learnings/auth-patterns.md
eve docs list --org $ORG_ID --prefix /agents/learnings/
# Search
eve docs search --org $ORG_ID --query "authentication retry"
```
Use for: curated knowledge, decision logs, learned patterns. Versioned (every update creates a new version). Emits `system.doc.created/updated/deleted` events on the event spine. Best for knowledge that is reviewed, refined, and shared.
**Agent Memory Namespaces** — curated knowledge stored as org docs with agent-scoped path conventions. Categories: `learnings`, `decisions`, `runbooks`, `context`, `conventions`. Supports confidence scores, tags, review dates, and expiration. Use for: accumulated expertise, decision logs, operational runbooks.
```bash
# Store a memory entry
eve memory set --org $ORG_ID --agent reviewer --category learnings --key "auth-retry-patterns" \
--content "Always use exponential backoff..." --confidence 0.9 --tags "auth,reliability" --review-in 30d
# Get a memory entry
eve memory get --org $ORG_ID --agent reviewer --key "auth-retry-patterns" --category learnings
# List entries
eve memory list --org $ORG_ID --agent reviewer --category learnings --limit 20
# Delete an entry
eve memory delete --org $ORG_ID --agent reviewer --category learnings --key "auth-retry-patterns"
# Search across memory (all agents or specific)
eve memory search --org $ORG_ID --query "auth retry patterns" --agent reviewer --limit 10
```
Namespace convention: `/agents/{slug}/memory/{category}/{key}.md` or `/agents/shared/memory/...`
**Org Filesystem** — shared per-org file storage mounted at `.org/` in agent workspaces and synced to local machines.
```bash
# Agents access .org/ directly in their workspace (all execution paths)
ls .org/ # browse org files
cat .org/shared/runbook.md # read shared knowledge
echo "new finding" >> .org/agents/reviewer/notes.md # write agent-scoped files
# Developers sync to local machines
eve fs sync init --org $ORG_ID --local ~/Eve/acme --mode two-way
eve fs sync status --org $ORG_ID
eve fs sync logs --org $ORG_ID --follow
```
Use for: large knowledge bases, design assets, documentation trees. Agents see `.org/` in their workspace regardless of execution path (agent-runtime or worker). Markdown-first defaults. Event-driven notifications (`file.created/updated/deleted`). Best for knowledge that lives as a file tree and benefits from both agent and human editing.
**Skills and Skillpacks** — distilled patterns packaged for reuse.
Use for: encoding recurring workflows and hard-won knowledge as reusable instructions. When an agent discovers a pattern worth preserving, distill it into a skill (see `eve-skill-distillation`). Skills are the highest-fidelity form of long-term memory — they don't just store information, they teach how to use it.
**Managed databases** — environment-scoped Postgres instances with agent-accessible SQL.
```bash
eve db sql --env $ENV --sql "SELECT key, value FROM agent_memory WHERE agent_id = 'reviewer' AND expires_at > NOW()"
eve db sql --env $ENV --sql "INSERT INTO agent_memory (agent_id, key, value) VALUES ('reviewer', 'last_review', '...')" --write
```
Use for: structured queries, relationship data, anything that benefits from SQL. Requires schema setup via migrations. Use `eve db rls init --with-groups` for access-controlled agent memory tables.
### Shared (coordination across agentRelated in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.