技能 人工智能 研究知识库:持久化知识管理

研究知识库:持久化知识管理

v20260805
research-wiki
这是一个持久化的、基于图谱的研究知识库。它能跨越整个科研生命周期,结构化地累积和关联知识,包括研究论文、实验结果、核心想法和可验证的论点。它通过知识网络不断迭代,确保每一次输入都能增强知识的深度,而非仅仅停留在一次性查询记录。
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概览

Research Wiki: Persistent Research Knowledge Base

Subcommand: $ARGUMENTS

Overview

The research wiki is a persistent, per-project knowledge base that accumulates structured knowledge across the entire ARIS research lifecycle. Unlike one-off literature surveys that are used and forgotten, the wiki compounds — every paper read, idea tested, experiment run, and review received makes the wiki smarter.

Inspired by Karpathy's LLM Wiki pattern: compile knowledge once, keep it current, don't re-derive on every query.

Core Concepts

Four Entity Types

Entity Directory Node ID format What it represents
Paper papers/ paper:<slug> A published or preprint research paper
Idea ideas/ idea:<id> A research idea (proposed, tested, or failed)
Experiment experiments/ exp:<id> A concrete experiment run with results
Claim claims/ claim:<id> A theorem/headline with an honest PROOF status — born via /proof-checker (see Hook 4)

Typed Relationships (graph/edges.jsonl)

Edge type From → To Meaning
extends paper → paper Builds on prior work
contradicts paper → paper Disagrees with results/claims
addresses_gap paper|idea → gap Targets a known field gap
inspired_by idea → paper Idea sourced from this paper
tested_by idea|claim → exp Tested in this experiment
supports exp → claim|idea Experiment confirms claim
invalidates exp → claim|idea Experiment disproves claim
supersedes paper → paper Newer work replaces older

Edges are stored in graph/edges.jsonl only. The ## Connections section on each page is auto-generated from the graph — never hand-edit it.

Capture hygiene (anti-self-poisoning)

Before persisting an idea / claim / experiment note, screen it for operational noise that would harden into a self-cited falsehood (see shared-references/capture-antipatterns.md). Resolve the helper via the canonical chain (integration-contract §2): .aris/tools/capture_filter.pytools/capture_filter.py$ARIS_REPO/tools/capture_filter.py (warn-and-skip if unresolved). Run python3 <capture_filter> - on the note text; if it flags env-failure / transient-error / negative-tool-claim, do NOT store it as a durable node — rewrite it to the fix / missing config / workaround, or drop it. Never store "codex/gemini/the reviewer can't do X" — that gets loaded into every future session and cited against the agent long after the real cause is gone. (The wiki's "failed ideas → anti-repeat memory" is the GOOD inverse: a class-level research finding, not operational noise.)

Wiki Directory Structure

research-wiki/
  index.md               # categorical index (auto-generated)
  log.md                 # append-only timeline
  gap_map.md             # field gaps with stable IDs (G1, G2, ...)
  query_pack.md          # compressed summary for /idea-creator (auto-generated, max 8000 chars)
  papers/
    <slug>.md            # one page per paper
  ideas/
    <idea_id>.md         # one page per idea
  experiments/
    <exp_id>.md          # one page per experiment
  claims/
    <claim_id>.md        # one page per testable claim
  graph/
    edges.jsonl          # materialized current relationship graph

Subcommands

Helper resolution (run before any subcommand below)

All wiki operations except plain directory bootstrap go through a single canonical helper, tools/research_wiki.py. Skills that touch the wiki must resolve $WIKI_SCRIPT via the chain below — never hard-code python3 tools/research_wiki.py …. Hard-coding silently fails when the project does not have tools/ on disk (the post-install_aris.sh default), which is exactly the failure mode that left a real user's research-wiki/ empty for a week.

cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
ARIS_REPO="${ARIS_REPO:-$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null)}"
if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
  ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
fi
WIKI_SCRIPT=".aris/tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || WIKI_SCRIPT="tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || { [ -n "${ARIS_REPO:-}" ] && WIKI_SCRIPT="$ARIS_REPO/tools/research_wiki.py"; }
[ -f "$WIKI_SCRIPT" ] || {
  echo "ERROR: research_wiki.py not found at .aris/tools/, tools/, \$ARIS_REPO/tools/, or via ~/.aris/repo." >&2
  echo "       Fix one of:" >&2
  echo "         1. rerun 'bash tools/install_aris.sh' from the ARIS repo (creates .aris/tools symlink, refreshes ~/.aris/repo)" >&2
  echo "         2. rerun 'bash tools/smart_update.sh' (refreshes ~/.aris/repo)" >&2
  echo "         3. export ARIS_REPO=<path-to-ARIS-repo>" >&2
  echo "         4. cp <ARIS-repo>/tools/research_wiki.py tools/" >&2
  exit 1
}

/research-wiki itself is the wiki tool — if the helper is missing the skill hard-fails. Caller skills that update the wiki as a side effect (/idea-creator, /result-to-claim, /research-lit, /arxiv, /alphaxiv, /deepxiv, /semantic-scholar, /exa-search) use the same chain but warn-and-skip instead of hard-failing — their primary output (idea list, claim verdict, paper summary) must still be delivered to the user.

/research-wiki init

Initialize the wiki for the current project. After resolving $WIKI_SCRIPT per the chain above:

python3 "$WIKI_SCRIPT" init research-wiki/

The helper creates research-wiki/{papers,ideas,experiments,claims,graph}/ plus index.md, log.md, gap_map.md, query_pack.md, and graph/edges.jsonl, then appends "Wiki initialized" to log.md.

(Earlier versions of this skill described a prose-only init that omitted query_pack.md — that drifted from the helper and made /idea-creator's Phase 0 query-pack check fall through to a rebuild_query_pack invocation that, under the old hard-coded path, silently failed. Delegating init to the helper is the single source of truth for the wiki schema.)

/research-wiki ingest "<paper title>" — arxiv: <id>

Add a paper to the wiki. This subcommand is thin wrapping around python3 "$WIKI_SCRIPT" ingest_paper …, which is the single implementation of paper ingest in ARIS (per shared-references/integration-contract.md — one helper, no copies). The helper does all of:

  1. Fetch metadata — queries the arXiv Atom API when --arxiv-id is given
  2. Generate slug<first_author_last_name><year>_<keyword>
  3. Check dedup — skip an existing page unless --update-on-exist
  4. Create pagepapers/<slug>.md with the schema below
  5. Rebuild index.md and query_pack.md
  6. Append log.md

Edge extraction (step 5/8 in the old manual flow) is not in ingest_paper; do it as a follow-up with add_edge per relationship identified:

# arXiv-known paper
python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
    --arxiv-id 2501.12345 --thesis "One-line claim from abstract."

# Venue paper with no arXiv mirror
python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
    --title "Attention Is All You Need" \
    --authors "Ashish Vaswani, Noam Shazeer, …" --year 2017 --venue "NeurIPS"

# Manual edge after ingest
python3 "$WIKI_SCRIPT" add_edge research-wiki/ \
    --from "paper:vaswani2017_attention_all_you" \
    --to "paper:chen2025_factorized_gap" \
    --type "extends" --evidence "Section 3.2: adapts the encoder block …"

Other skills (/research-lit, /arxiv, /alphaxiv, /deepxiv, /semantic-scholar, /exa-search) call the same helper directly in their own last step — they don't re-route through /research-wiki ingest as a subcommand, so they don't need an LLM roundtrip.

/research-wiki sync — arxiv-ids <id1>,<id2>,...

Batch backfill: ingest one or more arXiv IDs that were read earlier without being ingested (e.g., because research-wiki/ was set up after the reading happened, or a hook didn't fire).

# Explicit list
python3 "$WIKI_SCRIPT" sync research-wiki/ \
    --arxiv-ids 2310.06770,1706.03762

# From a file (one id per line, # comments ok)
python3 "$WIKI_SCRIPT" sync research-wiki/ --from-file ids.txt

Dedup is handled per-id; already-ingested papers are skipped silently. This is the recommended manual repair step (see integration contract §5 Backfill). sync does not scan session traces — callers declare the ids explicitly.

Paper page schema (exactly what ingest_paper emits — do not handwrite alternative fields; lint will flag drift):

---
type: paper
node_id: paper:<slug>
title: "<full title>"
authors: ["First A. Author", "Second B. Author"]
year: 2025
venue: "arXiv"
external_ids:
  arxiv: "2501.12345"
  doi: null
  s2: null
tags: ["tag1", "tag2"]
added: 2026-04-07T10:12:00Z
---

# <full title>

## One-line thesis

[Single sentence capturing the paper's core contribution]

## Problem / Gap

## Method

## Key Results

## Assumptions

## Limitations / Failure Modes

## Reusable Ingredients

[Techniques, datasets, or insights that could be repurposed]

## Open Questions

## Claims

[Reference claim pages: claim:C1, claim:C2, etc.]

## Connections

[AUTO-GENERATED from graph/edges.jsonl — do not edit manually]

## Relevance to This Project

[Why this paper matters for our specific research direction]

Additionally, when the paper was ingested via --arxiv-id and the arXiv API returned an abstract, the helper appends an ## Abstract (original) section after Relevance to This Project containing the raw abstract text as a blockquote. Manual ingests (no --arxiv-id) do not include this section.

/research-wiki query "<topic>"

Generate query_pack.md — a compressed, context-window-friendly summary:

Fixed budget (max 8000 chars / ~2000 tokens):

Section Budget Content
Project direction full sections Structured extraction from RESEARCH_BRIEF.md by ## heading (Problem / Constraints / Direction / Background / Non-Goals / Domain Knowledge / Existing Results), in priority order. No per-field char cap — the 8000-char assembly loop is the only safety net. Falls back to a flat 600-char slice if the brief uses no known headings.
Top 5 gaps 1200 chars From gap_map.md, ranked by: unresolved + linked ideas + failed experiments
Paper clusters 1600 chars 3-5 clusters by tag overlap, 2-3 sentences each
Failed ideas 1400 chars Always included — highest anti-repetition value
Top papers 1800 chars 8-12 pages ranked by: linked gaps, linked ideas, centrality, relevance flag
Active chains 900 chars limitation → opportunity relationship chains
Open unknowns 500 chars Unresolved questions across the wiki

Pruning priority (when over budget): low-ranked papers > cluster detail > chain detail. Never prune failed ideas or top gaps first.

Key rule: Read from short fields only (frontmatter, one-line thesis, gap summary, failure note). Do not summarize full page bodies every time.

/research-wiki update <node_id> — <field>: <value>

Update a specific entity:

/research-wiki update paper:chen2025 — relevance: core
/research-wiki update idea:001 — outcome: negative
/research-wiki update claim:C1 — status: refuted

After any update: rebuild query_pack.md, update log.md.

/research-wiki lint

Health check the wiki:

  1. Orphan pages — entities with zero edges
  2. Stale claims — claims still status: drafted or status: unproven older than 14 days
  3. Contradictions — claims with both supports and invalidates edges
  4. Missing connections — papers sharing 2+ tags but no explicit relationship
  5. Dead ideasstage: proposed ideas that were never tested
  6. Sparse pages — pages with 3+ empty sections

Output a LINT_REPORT.md with suggested fixes.

/research-wiki stats

Quick overview:

📚 Research Wiki Stats
Papers: 28 (12 core, 10 related, 6 peripheral)
Ideas: 7 (2 active, 3 failed, 1 partial, 1 succeeded)
Experiments: 12
Claims: 15 (8 verified, 4 unproven, 2 refuted, 1 sound-modulo-imports)
Edges: 64
Gaps: 8 (3 unresolved)
Last updated: 2026-04-07T10:12:00Z

Integration with Existing Workflows

All paper-reading skills follow the same integration contract (see shared-references/integration-contract.md):

  • single predicate — [ -d research-wiki/ ]
  • single canonical helper — python3 "$WIKI_SCRIPT" ingest_paper … after resolving $WIKI_SCRIPT via the chain at the top of this SKILL
  • concrete artifact — papers/<slug>.md + log.md entry
  • backfill — sync --arxiv-ids …
  • diagnostic — verify_wiki_coverage.sh (Policy E; resolved per integration-contract §2)

Hook 1: After /research-lit finds papers

# At end of research-lit, after synthesis:
if research-wiki/ exists AND $WIKI_SCRIPT resolved (chain at top of this SKILL):
    for paper in top_relevant_papers (limit 8-12):
        python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
            --arxiv-id <id> [--thesis "..."] [--tags "..."]
        for each explicit relation to existing wiki paper:
            python3 "$WIKI_SCRIPT" add_edge research-wiki/ \
                --from "paper:<slug>" --to "<target>" \
                --type <extends|contradicts|addresses_gap|...> \
                --evidence "..."
    log "research-lit ingested N papers"
elif research-wiki/ exists but $WIKI_SCRIPT did not resolve:
    warn "wiki update skipped — research_wiki.py unreachable; rerun install_aris.sh"

Each paper-reading skill ships its own Step "Update Research Wiki (if active)" that calls the same helper once per paper it touched. The business logic is not duplicated — only the loop over that skill's specific result set differs.

Hook 2: /idea-creator reads AND writes wiki

Before ideation:

if research-wiki/query_pack.md exists (and < 7 days old):
    prepend query_pack to landscape context
    treat failed ideas as banlist
    treat top gaps as search seeds
    still run fresh literature search for last 3-6 months

After ideation (CRITICAL — without it, ideas/ stays empty; runs on EVERY generation, including a re-run with updated constraints): the page write is a deterministic helper command, not a freehand step the model can skip:

for idea in all_generated_ideas (recommended + killed):
    python3 "$WIKI_SCRIPT" upsert_idea research-wiki/ \
      --slug <stable-id> --title <title> --stage <proposed|archived> --outcome pending \
      --thesis <...> --risks <...> --based-on <paper:slug,...> --target-gaps <G2,...>
    # one call: writes ideas/<slug>.md, wires inspired_by/addresses_gap edges,
    # rebuilds index + query_pack, logs. Default skip-on-exist (won't clobber an
    # existing idea enriched by /result-to-claim). `outcome` ∈ {unknown, pending,
    # negative, mixed, positive} — the experiment verdict is set later by
    # /result-to-claim, never guessed at ideation.
log "idea-creator wrote N ideas to wiki"

Hook 3: After /result-to-claim verdict

# Create/refresh the experiment node FIRST via the deterministic helper (verdict owner
# → --update-on-exist). This is the experiment BIRTH point. add_edge does NOT verify
# node existence, so GATE the supports/invalidates edges below on the node having been
# born (EXP_NODE_OK) — else they'd dangle off a missing exp node.
EXP_NODE_OK = (python3 "$WIKI_SCRIPT" add_experiment research-wiki/ --slug <exp_id> \
  --idea idea:<active_idea> --verdict <yes|partial|no> --confidence <high|medium|low> \
  --metrics <...> --reasoning <...> --provenance <run dir> --update-on-exist) succeeded
  # writes page + idea--tested_by-->exp edge + rebuilds index/query_pack

# Record empirical support as EDGES ONLY, and ONLY if EXP_NODE_OK — never overwrite the
# claim's `status`. A claim's `status` is the PROOF axis (verified / sound-modulo-imports
# / refuted / unproven / drafted / retracted), owned by /proof-checker (the claim birth
# point). Experiment support is a SEPARATE axis carried entirely by supports/invalidates
# edges; writing "supported"/"invalidated" into status is rejected by the validator.
if EXP_NODE_OK:
    for claim_id in resolved_claims:
        if verdict == "yes":
            add_edge(exp_id, claim_id, "supports")
        elif verdict == "partial":
            add_edge(exp_id, claim_id, "supports")   # partial — qualify in --evidence
        else:
            add_edge(exp_id, claim_id, "invalidates")

# Update idea outcome
update_idea(active_idea_id, outcome=verdict)

# If failed, record WHY for future ideation
if verdict in ("no", "partial"):
    update_idea failure_notes with specific metrics and reasons

rebuild query_pack
log "result-to-claim: exp_id updated, verdict=..."

Hook 4: Claim birth — from /proof-checker (the ONLY birth point)

Wiki claim nodes are born here. /proof-checker Phase 5.5 calls add_claim for each top-level theorem/headline after writing PROOF_AUDIT.json, stamping an honest PROOF-axis status and a provenance pointer to the audit trace. No other skill creates a claim node: /result-to-claim (Hook 3) only adds empirical supports/invalidates edges to an already-born claim and never edits its status.

# (run by /proof-checker; shown here for the wiki's record)
python3 "$WIKI_SCRIPT" add_claim research-wiki/ --slug thm-main-ub \
  --name "Main upper bound" --status verified \
  --provenance ".aris/traces/proof-checker/<run>/" --statement "..." --update-on-exist

Claim status ∈ {drafted, unproven, sound-modulo-imports, verified, refuted, retracted} — the proof axis only. Empirical support is a separate axis, carried entirely by edges (Hook 3), never written into status.

Re-ideation Trigger

After significant wiki updates, suggest re-running /idea-creator:

  • ≥5 new papers ingested since last ideation
  • ≥3 new failed/partial ideas since last ideation
  • New contradiction discovered in the graph
  • New gap identified that no existing idea addresses

The system suggests but does not auto-trigger. User decides.

Key Rules

  • One source of truth for relationships: graph/edges.jsonl. Page Connections sections are auto-generated views.
  • Canonical node IDs everywhere: paper:<slug>, idea:<id>, exp:<id>, claim:<id>, gap:<id>. Never use raw titles or inconsistent shorthands.
  • Failed ideas are the most valuable memory. Never prune them from query_pack.
  • query_pack.md is hard-budgeted at 8000 chars. Deterministic generation, not open-ended summarization.
  • Append to log.md for every mutation. The log is the audit trail.
  • Reviewer independence applies. When the wiki is read by cross-model review skills, pass file paths only — do not summarize wiki content for the reviewer.
  • The wiki is UTF-8. All wiki files are read and written as UTF-8 so a research-wiki/ stays portable across platforms and collaborators. A wiki created by an older ARIS on a non-UTF-8 locale (e.g. cp936 on Chinese Windows) must be converted to UTF-8 once — back it up first; the helper reports the offending file by name instead of guessing.

Acknowledgements

Inspired by Karpathy's LLM Wiki — "compile knowledge once, keep it current, don't re-derive on every query."

信息
Category 人工智能
Name research-wiki
版本 v20260805
大小 20.03KB
更新时间 2026-08-06
语言