Hyper memory
Use on-demand to extract evidence-anchored repo-local knowledge candidates from accumulated .hyperclaude/ artifacts (plans/done, plan-reviews, research) and curate them. Also when the user invokes /hyperclaude:hyper-memory. Orchestration-only — no Codex spawn.From its SKILL.md
npx -y skills add zeikar/hyperclaude --skill hyper-memoryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
- runs commandsInstructs the agent to run 3 commands, including `node "${CLAUDE_PLUGIN_ROOT}/scripts/memory/extract.mjs"` and 2 more.
SKILL.md
5.3 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it
hyper-memory
Repo-local knowledge extraction. Scans the accumulated .hyperclaude/ corpus and writes one evidence-anchored candidate markdown file per deterministic copy-based span under .hyperclaude/memory/candidates/. v1 is extraction + curation only — auto-injection into future sessions is the v2 north star and is explicitly out of scope here.
When to use
- User typed
/hyperclaude:hyper-memory(with or without an argument). - A batch of work has accumulated in
.hyperclaude/(several archived plans, plan-reviews, research artifacts) and it's worth mining for durable repo-local knowledge.
When to skip
- Only a single small artifact exists since the last extraction — not enough accumulated corpus to be worth mining.
- You want the knowledge injected automatically into a session — that's v2, not implemented.
How it works
-
Run
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory/extract.mjs"via Bash and parse the one-line JSON summary it prints to stdout:{ ok, scanned, candidates, written, skipped, errored, candidatesDir }.The script's CLI accepts exactly two flags — no others exist:
--dry-run— compute candidates and keys but write nothing (writtenis always0).--root <path>— corpus root to scan (default.hyperclaude).
-
It fully enumerates the v1 source allowlist — NOT newest-only:
plans/done/— every archived plan.plan-reviews/— every plan-review artifact whose verdict isShip as-is.research/— every research artifact.
code-reviews/anddocs-reviews/are v1 non-goals and are never scanned. -
It writes one evidence-anchored markdown file per candidate under
.hyperclaude/memory/candidates/, keyed by a compound hash so re-runs are idempotent: a candidate is skipped if its key already exists in EITHER.hyperclaude/memory/candidates/OR.hyperclaude/memory/promoted/— an already-promoted candidate is never resurrected.
Candidate schema
Each candidate file's YAML frontmatter carries exactly these keys, in this order:
plugin-version, type, source-artifact, anchors, mode, slug, git-head, generated, staleness
followed by a ## Claim (a deterministically templated one-liner) and a ## Evidence section holding strictly the verbatim copied span — never a generated or derived line.
CORE POLICY: artifact sentences are never stored as truth on their own — every candidate carries an inline evidence anchor quoted verbatim from source-artifact:, so a claim can always be traced back to the exact text it came from.
Two fields are easy to conflate and must be read as distinct:
source-artifact:— the.hyperclaude/**artifact path the candidate was mined from (evidence provenance; a gitignored artifact, not a canonical repo source).anchors:— a YAML list of live canonical repo source/doc paths the claim is about. The extractor ALWAYS emitsanchors: []— none of the three v1 sources deterministically names a real repo file, and a.hyperclaude/**path is NEVER a validanchors:entry.
Curation
Two locations only — no multi-state machine:
.hyperclaude/memory/candidates/— proposed, unreviewed..hyperclaude/memory/promoted/— human-accepted.
Promote: plain mv .hyperclaude/memory/candidates/<file> .hyperclaude/memory/promoted/<file> — NOT git mv (.hyperclaude/ is gitignored, so git tracks neither side).
Promotion gate: every candidate ships with anchors: []. Before promoting, the curator MUST add at least one real repo source/doc path (a non-.hyperclaude/ file that exists on disk) to the candidate's anchors: list. source-artifact: provenance alone never satisfies this gate — it names a gitignored artifact, not a canonical anchor.
Reject: rm the candidate file.
Idempotency: because promotion is a plain move out of candidates/, and the extractor checks BOTH candidates/ and promoted/ for an existing key, a promoted candidate is never re-created by a later extraction run.
Invocation argument
Invocation argument: $ARGUMENTS
Accepted argument grammar — nothing outside this table:
| Token(s) | Meaning |
|---|---|
--dry-run | compute candidates/keys, write nothing |
--root <path> | corpus root to scan (default .hyperclaude) |
The script's CLI parser rejects anything else (unknown flags, --root with a missing/flag-like value) with {"ok":false,"error":...} and a non-zero exit — see scripts/memory/extract.mjs.
Do NOT interpolate the raw $ARGUMENTS string into the Bash command. Parse it into individual tokens, keep only tokens matching the grammar above, and pass each as its own shell-quoted argument (e.g. quote the --root path value) when invoking node "${CLAUDE_PLUGIN_ROOT}/scripts/memory/extract.mjs". Any token outside the grammar means: do not pass it through — the script would reject it anyway.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most memory context skills give in ~1.2k tokens
Counted across 754 of the 1,056 authors here whose files we hold, read 2026-09-06
- Preserve existing content structurein 15 of 754, across 9 files
- Front-load the leading wordin 14 of 754, across 10 files
- Update existing entries instead of duplicatingin 14 of 754, across 7 files
- Keep CLAUDE.md under one hundred linesin 14 of 754, across 12 files
- Read CLAUDE.md at the project rootin 14 of 754
- Keep each meaning in a single source of truthin 12 of 754, across 8 files
- Redact sensitive information before committingin 11 of 754, across 4 files
- Scan for all CLAUDE.md filesin 11 of 754, across 7 files
- Use frontmatter for metadata on filesin 10 of 754, across 3 files
- Repeat user interactions 10 timesin 10 of 754, across 4 files
- Write the CLAUDE.md file into the target folderin 10 of 754, across 8 files
- Use memlab to process snapshotsin 9 of 754, across 3 files
Said here and by no other author read
- Run the extraction script via Bash
- Parse the one-line JSON summary
- Write one candidate markdown file per span
- Add at least one real repo path before promoting
- Move candidates to promote them
- Remove candidate files to reject them
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.