pr0fe5s0r/stixdb/cli
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Mandatory memory skill for all AI agents. Load this skill before answering any user request. StixDB is your PRIMARY and AUTHORITATIVE memory — check it before relying on training knowledge or conversational context. Covers: session startup/shutdown, storing discoveries, retrieving prior context, and ingesting files — all via the stixdb CLI.
Install
npx vskill@latest install pr0fe5s0r/stixdb/cliSKILL.md
StixDB CLI Memory Skill
Every session: load context from StixDB at the start, save everything learned at the end.Your context window is temporary. StixDB is permanent.
Session Structure (mandatory, every time)
Skipping step 2 means you answer blind. Skipping step 5 means everything learned is lost.
Step 0 — Resolve Collection Name (always first, never skip)
proj_$(basename $(pwd)) is a guess. Collection names may use hyphens where directory names use underscores, or differ entirely. Always verify:
Never proceed without setting `$COLL` from actual `collections list` output.
Windows PowerShell: use$COLL = "proj_your-actual-name"Windows CMD: useset COLL=proj_your-actual-nameAllstixdbcommands themselves are identical across platforms — only shell variable syntax differs.
Step 1 — Load Context
If the user gave you a specific task ("add X", "fix Y", "refactor Z"):
Run only the task-specific query. Skip orientation.
If you still find yourself reading files to orient after this, the query was too generic — re-run with the actual task name filled in.
If the user asked for orientation ("recap", "what's the state", "pick up where we left off"):
Before touching a specific area mid-session:
Retrieval Modes
stixdb search supports three modes. The default is hybrid — no flag needed.
| Mode | Flag | How it works | When to use | |
|---|---|---|---|---|
| hybrid (default) | --mode hybrid | Keyword scoring + vector similarity merged (0.7×semantic + 0.3×keyword). | Best general recall — use for all normal queries | |
| keyword | --mode keyword | Tag overlap (2× weight) + content term match. No API call. ~5ms. | Exact-tag lookups when you know the exact term | |
| semantic | --mode semantic | Vector embedding via API + cosine similarity. ~1–3s. | Paraphrase or conceptual queries that fail in keyword mode |
`stixdb ask` answer format: Answers are now Markdown with ## headers, bullet lists, inline citations [1] [2], and a Sources section. Use --stream to see tokens arrive progressively.
Query Rules
| Rule | Detail | |
|---|---|---|
| Always inject task context | "I am about to do X" gives retrieval a concrete anchor. "What was I doing?" matches nothing usefully. | |
Minimum --top-k for ask | Never below 10. Use 20–25 for orientation, 15–20 for area-specific, 10 for quick fact. | |
Use search for known facts | Faster, no LLM cost. Use ask only when synthesis across multiple nodes is needed. | |
| Check before storing | Always run stixdb search "[topic]" --top-k 5 before storing — if a match exists, supersede it, don't duplicate. |
If `ask` returns empty: either top-k is too low, the collection is wrong, or the question is too generic. Check with stixdb collections stats $COLL, then rerun with --top-k 25 and a more specific question.
Ingesting Files
Use stixdb ingest to make source files semantically searchable. Use stixdb store for knowledge you synthesize (decisions, patterns, bug fixes). Never mix them.
How to discover what to ingest
When to re-ingest
Re-ingest a file after significant changes so search returns current content, not stale chunks. Target specific files rather than the whole directory:
ingest vs store — which to use
Use ingest for | Use store for | |
|---|---|---|
| Source code files and directories | Decisions and their rationale | |
| README, docs, API specs | Bug root causes and fixes | |
| Any file whose content should be searchable | Coding patterns and conventions | |
| — | In-progress state and session summaries | |
| — | Architecture understanding you derived |
ingest creates searchable chunks of raw content. It does not store behavioral understanding, decisions, or experiential knowledge — you must write those with store.
What to Store vs What to Skip
✅ Store in StixDB
- File and module references (path + line range + purpose)
- Function/class behavioral contracts (what it does, not what it is)
- Decisions with rationale and rejected alternatives
- Bug root causes and exact fixes (file:line, symptom, fix)
- Discovered conventions and patterns
- In-progress state with exact next action
- API surface: inputs, outputs, side effects
❌ Never store
- Raw source code (use
ingestinstead, or store only the behavioral description + file:line reference) - Full conversation transcripts (distill into SESSION SUMMARY or DECISION entries)
- Transient debug output (store only if it reveals a root cause)
- Things directly readable from the filesystem (reference file:line instead)
- Vague summaries like "fixed bug in worker.py" (forces re-investigation — the exact failure mode StixDB prevents)
The test: Can the next agent read only this entry and continue work immediately, without opening a single file? If no — add more detail.
The SUPERSEDES Rule
Every time a fact changes, you MUST explicitly supersede the old entry. If you only add a new entry, both exist. The next agent retrieves both, cannot tell which is current, and picks arbitrarily. This is context contamination — it compounds silently and kills long-running projects.
Before storing any new entry, check:
If an existing entry covers the same topic, write a SUPERSEDES entry — not a duplicate:
Supersede when: a decision is reversed, a file moves, a bug reappears, a convention changes, an API contract changes, or in-progress work is completed.
Storage Templates
Fill every field. Abbreviated entries force re-investigation and defeat the purpose of StixDB.
Bug Fix
Decision
Pattern Discovered
Module Map
API Surface
Refactor
In-Progress
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/CLI/SKILL.md
Popularity
- Repository stars
- 75
- Repository forks
- 10
- 7-day trend score
- 0
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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