# Llm Wiki Research

> Research sprints, competitive deep dives, and auto-enrichment of stub wiki pages. Delegates web fetching to worker-source-fetcher. Files all findings back into the wiki.

- **Type:** Skill
- **Install:** `agentstack add skill-anh-chu-llm-wiki-pm-llm-wiki-research`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [anh-chu](https://agentstack.voostack.com/s/anh-chu)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [anh-chu](https://github.com/anh-chu)
- **Source:** https://github.com/anh-chu/llm-wiki-pm/tree/main/skills/llm-wiki-research

## Install

```sh
agentstack add skill-anh-chu-llm-wiki-pm-llm-wiki-research
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# LLM Wiki Research

Sub-skill of llm-wiki-pm. Handles research sprints, competitive deep dives, and auto-enrichment of stub entities. Delegates all URL fetching to `worker-source-fetcher` so privacy filtering and raw/ logging happen correctly.

**WebFetch note:** `WebFetch` is listed in allowed-tools for quick page previews (e.g., confirming a URL before delegation). For source capture (saving to raw/), always delegate to `worker-source-fetcher`. Never call WebFetch directly for source saving — privacy filtering and raw/ logging won't happen.

## Orient First

Orient per AGENTS.md before any writes:

1. Read `$WIKI/SCHEMA.md`
2. Read `$WIKI/index.md`
3. Read last 20-30 lines of `$WIKI/log.md`
4. Read `$WIKI/overview.md`

Research sprints may create many pages. Get user confirmation before creating 5+ pages.

## Wiki Path Resolution

```bash
WIKI=$(cat .wiki-path 2>/dev/null | tr -d '[:space:]')
WIKI=${WIKI:-${CLAUDE_PLUGIN_OPTION_wiki_path:-${WIKI_PATH:-$(pwd)}}}
```

## Worker Delegation

This skill uses `worker-source-fetcher` for all URL fetching. Never call WebFetch directly for source capture — always invoke the worker:

> "Use worker-source-fetcher to fetch [URL]"

This ensures privacy filtering and raw/ logging happen correctly. The worker returns:
`"OK: saved to raw//.md"` — use that path for synthesis.

---

## Operation 1: Research Sprint

**Trigger:** "research sprint on [topic]", "deep research on [topic]"

**① Define scope**

Confirm with user:
- What is the topic / question to answer?
- Target depth: surface / standard / deep
- Time budget (number of sources)

**② Wiki-first**

```bash
grep -r "" $WIKI --include="*.md" -l
```

Read all relevant pages. Surface: "Wiki has N relevant pages. Here's what we already know: [...]. Gaps: [...]."

**③ Research plan**

Present 3-5 specific sources to fetch — name each, why it's relevant, what question it answers. Typical: analyst reports, company pages, recent press, whitepapers, industry forums. Get user confirmation before fetching.

**④ Delegate fetching**

For each confirmed source: "Use worker-source-fetcher to fetch [URL]"

If a fetch fails (404, paywall, timeout), note it and continue. Collect all raw/ paths before writing.

**⑤ Synthesize**

Read all fetched raw files. Extract entities, claims, data points. Cross-reference against existing wiki pages. Distinguish:
- Confirmed (claim now in 2+ independent sources)
- New (single source, not yet corroborated)
- Contradicts wiki (surface the conflict explicitly)

**⑥ File findings**

Create/update wiki pages per core ingest discipline: inline provenance, coverage markers, confidence levels, min 2 outbound wikilinks, backlink audit.

Produce a synthesis page at `queries/research--/README.md`:

```markdown
---
title: "Research Sprint: "
created: YYYY-MM-DD
type: query
tags: []
sources: []
---

## Scope
Question: [...]  Depth: [...]  Sources: N

## What We Knew
[Pre-sprint wiki state summary]

## What We Learned
[Net-new findings with inline citations]

## Confirmations
[Claims now corroborated by 2+ sources]

## Contradictions
[Conflicts with existing wiki pages — cite both sides]

## Still Unknown
[Gaps that fetching didn't resolve]

## Pages Created/Updated
- [[slug]]: [brief note]
```

**⑦ Surface delta**

What did we learn that we didn't know? What did it confirm? What's still unknown? Any contradictions with the wiki?

**⑧ Log**

```
## [YYYY-MM-DD] research-sprint | topic:  | sources: N | pages created/updated: N
```

---

## Operation 2: Competitive Deep Dive

**Trigger:** "competitive deep dive on [company]", "full competitive analysis of [company]"

**① Read existing coverage**

Read `$WIKI/entities/.md` and related `comparisons/` pages. If `coverage: comprehensive`, ask: "Already marked comprehensive — update pass or fresh deep dive?"

**② Research plan**

Standard source set:
- Official website (product, pricing, about)
- Recent press (last 6-12 months)
- Job postings (signals: what they're building)
- Pricing page
- G2 / Gartner / Capterra reviews
- Analyst mentions (MQ, Wave, IDC)
- Crunchbase / LinkedIn (funding, headcount)

Get user confirmation before fetching.

**③ Delegate fetching**

"Use worker-source-fetcher to fetch [URL]" for each confirmed source.

**④ Update entity page**

Apply diff discipline (core §4): snapshot to `_archive/-.md` first, show diff before writing, update inline provenance on revised facts, sweep stale variants.

**⑤ Update comparison pages**

Update existing comparisons/ pages. Offer to create a new comparison page if the deep dive reveals strong differentiation.

**⑥ Flag confidence by source**

| Source type | Confidence |
|---|---|
| Official website, press releases | `verified` |
| Analyst reports, G2 reviews | `likely` |
| Forums, social media, unofficial blogs | `rumor` |

**⑦ Log**

```
## [YYYY-MM-DD] competitive-deep-dive | entity:  | sources: N | pages updated: N
```

---

## Operation 3: Auto-Research (Stub Enrichment)

**Trigger:** "auto-research [entity]", "enrich [entity]", "fill in [entity] page"

For entity pages with `coverage: stub`. Fast enrichment pass. This is *factual/web*
enrichment. If the user wants relationship/CRM context (tier, touchpoint, feature
asks) rather than facts, route to llm-wiki-crm's enrich instead.

**① Read the stub** — what do we already know? What's in `gaps:`?

**② Search**

```
WebSearch: "[entity name]" recent news
WebSearch: "[entity name]" official website
WebSearch: "[entity name]" [primary domain, e.g. pricing / funding / product]
```

**③ Extract** — description, key facts, relationships to other wiki entities, recent events.

**④ Update stub page** with inline provenance `[source: url, date]`. Bump `coverage:` stub → partial if meaningful data found. Update `gaps:` and `sources:` frontmatter. Bump `updated:`.

Do NOT fabricate. If search returns nothing useful, say so. Leave `coverage: stub`.

**⑤ Log**

```
## [YYYY-MM-DD] auto-research | entity:  | coverage: stub→partial | sources: N
# or if nothing found:
## [YYYY-MM-DD] auto-research | entity:  | no public data found | coverage: stub (unchanged)
```

---

## Operation 4: Gap Research

**Trigger:** "research our gaps", "fill coverage gaps", "research stubs"

**① Scan for stubs**

```bash
grep -r "coverage: stub" $WIKI --include="*.md" -l
grep -rL "coverage:" $WIKI/entities $WIKI/concepts --include="*.md"
```

**② Present list** — ask user which to prioritize.

**③ Run Operation 3** on each selected stub in sequence. Surface result before moving to next: "Enriched [[entity]] — stub → partial. Found: [key facts]. Continue?"

**④ Report**

```
Gap research complete:
- N pages enriched (stub → partial)
- N pages still stub (insufficient public data)
- N pages skipped
```

**⑤ Log**

```
## [YYYY-MM-DD] gap-research | stubs scanned: N | enriched: N | still-stub: N
```

---

## Pitfalls

- **Orient first**: before any writes. Research sprints may touch many pages.
- **Delegate fetching**: always use `worker-source-fetcher` — never WebFetch directly for source saving.
- **Confirm before mass creates**: 5+ pages → user confirmation first.
- **Inline provenance**: every non-obvious claim needs `[source: slug, location]`.
- **Coverage markers**: bump `coverage:` after meaningful enrichment.
- **Confidence discipline**: verified / likely / rumor — label accordingly.
- **No fabrication**: if search returns nothing, say so.
- **Snapshot before destructive updates**: `_archive/-.md` before deep dive overwrites.
- **Dedup**: grep before creating. Confirm update vs create.
- **Privacy**: customer names, deal sizes, 1:1 content → `private: true`.
- **Synthesis page**: research sprints always produce `queries/research--/README.md`.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [anh-chu](https://github.com/anh-chu)
- **Source:** [anh-chu/llm-wiki-pm](https://github.com/anh-chu/llm-wiki-pm)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-anh-chu-llm-wiki-pm-llm-wiki-research
- Seller: https://agentstack.voostack.com/s/anh-chu
- Browse the marketplace: https://agentstack.voostack.com/browse

---
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