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:

• Inventing a date ("March 2026 post", "€5M Series A in April 2026") without

a URL or raw/ file that says so.

• Inventing a connection point ("HEC Paris alum", "both at Stripe") unless

you can cite a line in kb/me/self.md or kb/me/org.md.

• Claiming you wrote a KB page without running the write command and

reading the file back.

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:

• slug — kb_page.py style: lower-case name, non-alnum → -, e.g.

alice-chen. Disambiguate with company if needed (alice-chen-stripe).

• display_name
• company (if known) → compute an org slug the same way (acme-corp)

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.

1. 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.

1. 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:

• Block 2's gate must pass before you touch block 3. Orgs delta zero = STOP.
• Never paraphrase a script's stdout. Paste it as-is.
• Never claim a KB write that isn't visible in the post-counts or log tail.
• Use enrich_titles only when the user asks for richer contact coverage —

leadbay_pull_leads already returns a recommended contact per lead.

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" "<email>"

• private (gmail, hotmail, yahoo, proton, yandex, icloud, …): the email

is a personal mailbox. Do NOT set company from this domain. Use

LinkedIn / Leadbay / the target's own statements instead.

• isp (comcast, bt, verizon, cox, …): residential internet provider —

same rule. Do NOT infer employer.

• school (.edu, .ac.uk, hec.fr, mit.edu, stanford.edu, …): academic

affiliation. Note it on the page as ## Affiliations (school, not

current employer) but do NOT treat as employer unless the target is

confirmed faculty/staff.

• corporate: the domain IS the company. Use company_slug_from_domain

result as the kb/orgs/.md target. Confirm by cross-checking

LinkedIn / company URL when available.

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:

For every match, record:

• Date of last interaction
• Direction (sent-by-user | received-from-target)
• Channel
• A one-line summary (don't paste the body — PII)

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<company-slug>\b" ~/.openclaw/outclaw/kb/people/*.md
# Or the org's own backlinks:
python3 "$SHARED/scripts/kb_search.py" --slug org:<company-slug>

- 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/<slug>.md \
         ~/.openclaw/outclaw/kb/orgs/<orgslug>.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