Outclaw Research

OutClaw — Research

FIRST ACTION RULES — read before anything else

1. Discovery intent (user said "get me leads / pull leads / prospects / outreach plan")? Plans are delivered in daily batches of 10–15 fresh targets, not 1–3. Three is noise for a salesperson at a 5% reply rate. Use the batch flow:

# a) Pull + save the Leadbay response, then let the batch script do the
   bulk work (tier-1 persist for every lead, fresh-pick top N, emit
   manifest).
Agent: call leadbay_pull_leads (no args) → save JSON → /tmp/leadbay-pull.json
bash ~/.openclaw/skills/outclaw/shared/scripts/outclaw_daily_batch.sh --n 15 --stale-after-days 7
b) DEFAULT: skip Tier-2 for the full batch. Tier-1 bodies now carry the
   Leadbay AI qualification_summary + tags + recommended contact (see
   leadbay_tier1_persist.py's richer body format) — enough for Day-1
   drafts. Tier-2 research is OPT-IN for the ~top 3 the user wants to
   go deeper on (costs ~3 min / lead via leadbay_research_lead).
c) Build the Day-1 scaffold for all 15 targets. Scaffolder pulls angle
   hooks from each Tier-1 body (no Tier-2 required) + on-brand copy +
   sender identity.
python3 ~/.openclaw/skills/outclaw/shared/scripts/plan_scaffolder.py --max 15
Output: /tmp/outclaw-plan-draft.md

After the scaffold is written, the agent's remaining work is only writing the 15 Day-1 email bodies + Provenance blocks (no research, no bookkeeping), then running channel_validator.py + draft_checker.py, then presenting. See outclaw-plan SKILL.

Tier-2 is opt-in. When the user says "go deeper on " or "research more", THEN call leadbay_research_lead + leadbay_tier2_persist.py for that specific target. Do NOT Tier-2 the full batch by default — the turn budget won't cover 15 × 3-min research calls.

2. Targeted research intent (user named a specific person/company)? Start at "Step 1 — Parse the input into a target" below.

3. Never fabricate. Every fact in a KB page body, plan angle, or draft email MUST be traceable to a raw source file under ~/.openclaw/outclaw/kb/raw/ or kb/me/. If you can't cite the file, you can't include the fact. (See § Zero-hallucination rule.)

4. No promise-then-silent turn closes. Do NOT end a turn with "I'll spin on that now", "surface shortly", "standby", "more to come". That pattern is a silent failure — the agent yields control and never returns. Either finish the work in this turn and present the results, or stop cleanly at the last completed step with a short "I've done X / Y is next — want me to continue?". The draft_checker.py promises-regex rejects plans containing these phrases.

Your job: given a person (name, LinkedIn, email, company) or a discovery intent ("find me someone at Acme worth talking to"), use every available tool to build a rich, persistent profile and store it in the KB.

Output quality bar: ≥3 concrete, recent (≤30 day) signals per target + a section cross-referencing the target with kb/me/ (mutual orgs, schools, topics, connections). If you can't hit that bar, explicitly say what you were blocked on — never paper over thin research with fluff.

Use the tools you actually have

Check your own tool list at session start. Your ordering preference:

1. leadbay_research_lead / leadbay_research_company — if available, use first 2. web_search + web_fetch — baseline every OpenClaw agent has these 3. read (for local caches under kb/raw/) 4. User-provided text pasted into the conversation

If leadbay_* isn't in your tool list, that's fine — use web_search to find the target's LinkedIn/Twitter/company page, web_fetch the specific pages, and write what you actually learn into raw/-.md. Never insist on a tool that isn't in your active tool list. Stating "Leadbay isn't connected" is correct; pretending you used it is a hallucination failure.

Resolver mandate (non-negotiable)

Before creating or modifying any page under ~/.openclaw/outclaw/kb/ or any entry in memory//memory.jsonl, read shared/references/RESOLVER.md and file by primary subject, not by source format or skill name. Use shared/scripts/kb_ingest.py + kb_page.py — do not hand-craft file paths. Research facts go in kb/{people,orgs,topics,places}/; runtime observations ("email bounced") go in per-tenant memory, not the KB.

Zero-hallucination rule (non-negotiable)

Every signal, hook, career fact, org fact, and connection point MUST be traceable to a real source — either a URL you fetched or a file you wrote under ~/.openclaw/outclaw/kb/raw/. If you cannot point at a real source, do NOT write the fact. Leave the field empty and list it under gaps[] in your return.

Specifically forbidden:

Producing plausible-sounding content you can't source is a hard failure caught by the verification gate below.

Preamble (skip if called from orchestrator)

SHARED="$(dirname "$(dirname "$(cd "$(dirname "$0")" && pwd)")")/shared"
bash "$SHARED/scripts/memory_search.sh" --type tool_inventory --limit 1
cat ~/.openclaw/outclaw/kb/me/self.md 2>/dev/null
cat ~/.openclaw/outclaw/kb/me/org.md  2>/dev/null

Flow

Step 1 — Parse the input into a target

The user gave you some combination of: name, LinkedIn URL, email, company, title, company URL. From these, compute:

Discovery intent (e.g. "get me some leadbay leads", "pull a promising lead", "purchase contacts for the best ones"):

Leadbay is a sales inbox, not a queryable database. See shared/references/leadbay-integration.md for the full mental model. Key rules:

1. NEVER ask the user for "targeting criteria" (industry, company size, geography, lead count, job titles). The user's ICP is already configured inside Leadbay. Asking for criteria = you're thinking of Leadbay as a DB, which it isn't. 2. NEVER ask which titles to enrich when the user says "recommended contacts" or "the best contacts" — leadbay_enrich_titles auto-picks based on the ICP. Recommended means Leadbay chooses. 3. Verify your tool list FIRST. Before attempting any Leadbay operation, check that leadbay_pull_leads (or at minimum leadbay_account_status) is in YOUR active tool list — not just plugins.entries.leadclaw. If the composite tools aren't bound to your agent, refuse per the template in leadbay-integration.md §"What to do when the composite tools aren't in your tool list".

The canonical flow — four tool-call blocks, no improvisation:

The flow is written so the agent only decides which lead_ids to deep-research. Everything else is driven by helper scripts. Execute each block; paste the literal stdout to the user. Do not paraphrase.

# --- Block 1: pre-counts + pull ---
BEFORE_ORGS=$(ls ~/.openclaw/outclaw/kb/orgs/ 2>/dev/null | wc -l | tr -d ' ')
BEFORE_PEOPLE=$(ls ~/.openclaw/outclaw/kb/people/ 2>/dev/null | wc -l | tr -d ' ')
echo "before: orgs=$BEFORE_ORGS people=$BEFORE_PEOPLE"

Then call the MCP tool leadbay_account_status, followed by leadbay_pull_leads (no args). Save the pull response JSON to /tmp/leadbay-pull.json using your Write tool.

# --- Block 2: Tier-1 persist + verification gate (MANDATORY) ---
python3 ~/.openclaw/skills/outclaw/shared/scripts/leadbay_tier1_persist.py \
  --from-file /tmp/leadbay-pull.json
AFTER_ORGS=$(ls ~/.openclaw/outclaw/kb/orgs/ | wc -l | tr -d ' ')
AFTER_PEOPLE=$(ls ~/.openclaw/outclaw/kb/people/ | wc -l | tr -d ' ')
N_LEADS=$(python3 -c 'import json; print(len(json.load(open("/tmp/leadbay-pull.json")).get("leads",[])))')
echo "after: orgs=$AFTER_ORGS (+$((AFTER_ORGS-BEFORE_ORGS))) people=$AFTER_PEOPLE (+$((AFTER_PEOPLE-BEFORE_PEOPLE))) / leads_pulled=$N_LEADS"
GATE: the orgs delta MUST be > 0 while N_LEADS > 0. If zero, STOP — the
persist step was skipped. Do not continue to block 3.
--- Block 3: pick top N to deep-research (freshness-aware) ---
python3 ~/.openclaw/skills/outclaw/shared/scripts/leadbay_top_picks.py \
  --from-file /tmp/leadbay-pull.json --n 15 --stale-after-days 7

This returns {ids: [...], summaries: [...], skipped_recent: [...]}. The skipped_recent array names any orgs we drafted a plan for in the last 7 days — they are INTENTIONALLY deprioritised so the user sees fresh targets day-to-day. Show the skipped list to the user with a note: "Still in flight from — include anyway?" Only re-add to the plan if the user says yes.

Tier-2 research is OPT-IN — do NOT run it for the full batch by default. The Tier-1 body already carries the Leadbay AI qualification excerpt + tags + contact, which is enough for a Day-1 draft. Only call leadbay_research_lead when the user says "go deeper on " for a specific target.

# --- Block 4: Tier-2 persist (per researched lead) ---
for f in /tmp/leadbay-research-*.json; do
  python3 ~/.openclaw/skills/outclaw/shared/scripts/leadbay_tier2_persist.py --from-file "$f"
done
Final audit
ls ~/.openclaw/outclaw/kb/orgs/ | wc -l
ls ~/.openclaw/outclaw/kb/people/ | wc -l
tail -6 ~/.openclaw/outclaw/kb/log.md

After block 4, hand off to outclaw-plan with the list of slugs for the top picks. Plan draws EVERY concrete fact from the Tier-2 org/person pages — no improvised claims, no [Your Name] / [Your Company] placeholders, no fabricated "recent Series C" unless it's on the page.

Non-negotiable rules:

If you find yourself writing the words *"what industry"*, *"what size"*, *"which titles"*, STOP. You're asking the wrong question. Read shared/references/leadbay-integration.md again.

Step 2 — Check KB first

python3 "$SHARED/scripts/kb_search.py" --slug person:$SLUG

If an entry exists and its last_updated is ≤30 days, return it and ask the user if they want a refresh. If yes, proceed. If no entry, proceed.

Step 2.25 — Email-domain discipline

If you have an email address for the target, classify the domain BEFORE deriving a company from it:

python3 "$SHARED/scripts/domain_classifier.py" ""

Example wrong inference to avoid: "alice@gmail.com" → org slug "gmail". The classifier catches that; the skill must ACTUALLY call the classifier, not eyeball the domain.

Step 2.5 — Cross-reference: past conversations + same-company people

Before running fresh external research, **sweep local context you already have**:

a. Past conversations with THIS person. Query every connected communication-capable tool for threads where the target appears as sender or recipient. Priority order:

| Tool in inventory | Query | |-------------------|-------| | gog (Gmail) | gog gmail messages search "from: OR to:" --max 50 -j | | email-mcp | same search via the MCP's search endpoint | | slack-mcp-server / slack | slack search --user --max 50 | | whatsapp-mcp-ts / wacli | search conversation history by phone | | telegram-mcp | search chats where counterparty matches handle | | mac_messages_mcp / imsg | iMessage/SMS history by phone or contact | | discord-mcp | DM history by user id | | linkedin-cli | InMail / message history with the profile URL | | apple-notes / things-mac | search for user's own prior notes about the target |

For every match, record:

Drop a raw/ snippet if the thread is substantive: kb_ingest.py begin person --note "prior-thread--:

- 2025-11-14 · Gmail · user → target · "Intro from David, re: ICP pilot"
2026-02-03 · LinkedIn DM · target → user · "Circling back after SaaStr Annual"

# List all people with this org in their connections
grep -l "orgs: .*\b\b" ~/.openclaw/outclaw/kb/people/*.md
Or the org's own backlinks:
python3 "$SHARED/scripts/kb_search.py" --slug org:

- Bob Smith (CTO, kb/people/bob-smith.md) — active thread Mar 2026, warm
Carol Wong (VP Sales, kb/people/carol-wong.md) — opted out 2025-10

for p in ~/.openclaw/outclaw/kb/people/.md \
         ~/.openclaw/outclaw/kb/orgs/.md \
         ~/.openclaw/outclaw/kb/index.md \
         ~/.openclaw/outclaw/kb/log.md; do
  echo "--- $p ---"
  /usr/bin/head -40 "$p" 2>/dev/null || echo "MISSING: $p"
done