eval

name	eval
description	Test harness for the Signal Prospecting Kit v4.1. Runs deterministic checks and rubric-based grading against all 6 skills including tool connections, multi-batch flow, LinkedIn outreach, channel selection, self-improvement loop, enrichment tiers, bridge/CTA variation, variation planning, and fallback tool detection. Triggers: /eval, /eval all, /eval {skill-name}, /eval simulate. Does NOT require WebSearch — validates structure, rules, and simulated output.
allowed-tools	["Read","Write","Edit","Grep","Glob","Bash","Agent"]

/eval — Signal Prospecting Kit v4.1 Test Harness

You are a testing agent. You evaluate the Signal Prospecting Kit by reading each SKILL.md, checking against deterministic rules, simulating scenarios, and scoring output quality. Strict, specific, every failure gets a fix.

---

Running Evals

/eval all — Full test suite. /eval structure — File structure and frontmatter only. /eval start — Orchestrator tests. /eval profile — Market research tests. /eval signal-scout — Signal discovery tests. /eval prospect — Company + contact + enrichment tests. /eval outreach — Email + LinkedIn + batch variation tests. /eval push — Export + deliverability + learnings tests. /eval simulate — Full simulated output grading only.

Default: run all.

---

Test Suite 1: Structure

1.1 Directory Layout

Check exists (inside .claude/skills/):
  ✓ .claude/skills/start/SKILL.md
  ✓ .claude/skills/profile/SKILL.md
  ✓ .claude/skills/signal-scout/SKILL.md
  ✓ .claude/skills/prospect/SKILL.md
  ✓ .claude/skills/outreach/SKILL.md
  ✓ .claude/skills/push/SKILL.md
  ✓ README.md (at repo root)

Must NOT exist in distributed kit:
  ✗ eval/ (dev only)
  ✗ gtm/ (created at runtime)
  ✗ install.sh (no longer needed)

1.2 Frontmatter Validity

For each SKILL.md:

  ✓ Valid YAML frontmatter (--- delimiters)
  ✓ 'name' field matches directory name
  ✓ 'description' mentions: triggers, reads, writes, standalone
  ✓ 'allowed-tools' is non-empty list
  ✓ All listed tools exist in Claude Code
  ✓ WebSearch/WebFetch for skills that research
  ✓ Write/Edit for skills that create files

1.3 No Leaked Secrets

Grep all files except eval/:

Must NOT match:
  ✗ /[A-Z_]*(KEY|TOKEN|SECRET)\s*[:=]/ (actual API keys)
  ✗ /Users/ (absolute paths)
  ✗ Deepline, deeplineagent, Exa API, Apify, ScrapeCreators
  ✗ Julien-specific references in SKILL.md files
  ✗ Tool names in outreach OUTPUT (Clay, Instantly, HeyReach)
    — allowed only in "don't mention these" rules

Note: API key REFERENCES are fine (e.g., "$APOLLO_API_KEY",
"API Keys Available section"). Actual key VALUES are not.

1.4 README Quality

  ✓ Install: clone + cd + claude (3 lines)
  ✓ Quick start shows all 6 stages
  ✓ Mentions all 6 skills by name
  ✓ Mentions approval gates + auto-continue
  ✓ Mentions LinkedIn outreach as a channel option
  ✓ Mentions tool connections (Clay, Apollo, Hunter, Instantly)
  ✓ Mentions the learning loop + multi-batch progression
  ✓ Has CTA to climategrowthadvisors.com
  ✓ Under 1200 words
  ✓ No broken markdown links

1.5 Cross-Skill Consistency

  ✓ All skills reference ./gtm/ path
  ✓ Consistent file names: company.md, icp.md, voice.md,
    signals.md, prospects.md, learnings.md
  ✓ Routing chain: start → profile → signal-scout →
    prospect → outreach → push
  ✓ Auto-continue after each stage (no manual /command needed)
  ✓ Approval gates at: profile, signal-scout, prospect, outreach
  ✓ All skills show "what was loaded" before working
  ✓ All skills work standalone (graceful degradation)

Anti-signal data flow:
  ✓ /start collects lost deals in Q2 (optional)
  ✓ /start saves Lost Deal Anti-Signals to icp.md
  ✓ /signal-scout reads lost deals from icp.md
  ✓ /signal-scout generates anti-signal list + competitor list
  ✓ /signal-scout saves anti-signals to signals.md
  ✓ /prospect reads anti-signals from signals.md
  ✓ /prospect applies anti-signal penalties in scoring
  ✓ /prospect shows Flagged + Dropped sections with anti-signal reasons
  ✓ Flow works if lost deals are empty (theoretical anti-signals used)

Tool-agnostic enrichment flow:
  ✓ /start asks about email enrichment conversationally (no hardcoded tools)
  ✓ /start does NOT recommend specific software unprompted
  ✓ /prospect uses whatever tools are connected, no preference hierarchy
  ✓ /prospect pattern-guesses emails when no enrichment tools available
  ✓ /prospect marks contacts "LinkedIn only" when no email found
  ✓ /outreach writes LinkedIn-only for contacts without email
  ✓ /push shows email status breakdown (verified / pattern-guess / LinkedIn only)
  ✓ /push does NOT hardcode recommendations for specific tools

Orchestrator resilience:
  ✓ All 6 skills have "Handling Questions and Tangents" sections
  ✓ Users can ask "what tool should I use?" and get researched answer
  ✓ Users can skip ahead (skills ask for what they need inline)
  ✓ Users can go off-topic and resume with "continue"
  ✓ Approval gates handle rejection with re-research, not just deletion
  ✓ /start returning mode updates icp.md when new tools detected
  ✓ /prospect handles mid-session tool changes and ICP changes
  ✓ /outreach handles mid-flow tool connection (re-enriches LinkedIn-only)
  ✓ /signal-scout standalone creates minimal icp.md for downstream
  ✓ /prospect standalone generates signals inline if signals.md missing
  ✓ /push adapts format menu and deliverability to user's actual stack

---

Test Suite 2: /start

2.1 First-Run Onboarding

  ✓ Shows empty state scan with all 6 context files
  ✓ Empty state includes plain-english descriptions for jargon terms
    (ICP Profile → "your ideal customer", Signal Types → "events that
    suggest someone needs your product")
  ✓ Q1 uses "email sending tool" not "sequencer"
  ✓ Asks exactly 2 compound questions
  ✓ Q1 covers: domain, ICP, stack, do-not-contact
  ✓ Q1 does NOT ask about API keys (auto-detected in Step 3)
  ✓ Q2 covers: cold emails that got replies + deals won + deals LOST
  ✓ Q2 does NOT say "paste a writing sample" (old version)
  ✓ Lost deals marked as optional but valuable
  ✓ Accepts partial answers gracefully
  ✓ Researches company domain via WebSearch/WebFetch

2.2 Tool Detection (CRITICAL — must not be skipped)

  ✓ Step is marked CRITICAL, DO NOT SKIP in SKILL.md
  ✓ Runs silent detection (Bash for env vars, MCP tool check)
  ✓ NEVER displays or logs API key values
  ✓ Notes tools user mentioned in stack answer
  ✓ Asks about email enrichment conversationally if none detected
  ✓ Does NOT recommend specific software unprompted
  ✓ If user asks "what tool?", researches and gives honest answer
  ✓ Handles "I don't have one" gracefully (pattern-guess + LinkedIn)
  ✓ Shows TOOLS output block (connected / mentioned / no enrichment)
  ✓ Saves to Connected Tools section in icp.md
  ✓ Does NOT gate anything on tool connections
  ✓ Foundation Built includes "Email enrichment: {tool or pattern-guess}"

2.2b No-outbound fallback

  ✓ If user has no cold emails and no deals, skill proceeds gracefully
  ✓ Voice.md built from website copy and LinkedIn instead
  ✓ Voice.md includes note "Built from website copy — provide example anytime"
  ✓ Signals built from market research (theoretical) instead of won deals

2.3 Files Created

company.md sections:
  ✓ Domain, Product, Positioning, Claimed Customers,
    Differentiators, Stage, Researched

icp.md sections:
  ✓ What We Sell, Target Buyer, Buyer's Situation,
    Scoring Criteria, Pain Indicators
  ✓ Stack (CRM, email sending tool, LinkedIn, email finder)
  ✓ Connected Tools (tool name, status, what it enables)
  ✓ Do Not Contact (existing customers, past contacts)
  ✓ Won Deal Patterns (from Q2 deal examples):
    - Per deal: Buyer, Trigger, Closer, Signal
    - Patterns section (what deals have in common)
  ✓ Lost Deal Anti-Signals (from Q2 lost deal examples):
    - Per loss: Buyer, Why didn't buy, Anti-signal
    - Anti-Fit Patterns section (what losses have in common)
    - Section empty if user skipped lost deals (not an error)

voice.md sections:
  ✓ Name (from sign-off)
  ✓ Extracted From, Tone, Patterns
  ✓ Signature Moves (from reply-getting emails)
  ✓ What Got Replies (what specifically worked)
  ✓ Avoid

company.md vs icp.md no overlap:
  ✓ company.md: Product, Claimed Customers (from THEIR site)
  ✓ icp.md: What We Sell, Target Buyer (USER's words)

2.4 Returning Mode

  ✓ Shows batch history with reply rates per batch
  ✓ Shows overall cumulative stats
  ✓ Shows top pattern + what to avoid from learnings
  ✓ Flags unlogged results ("N prospects sent, no results logged")
  ✓ Priority 1: Offer structured result logging if unlogged sends exist
  ✓ Priority 2: Route to incomplete pipeline step
  ✓ Priority 3: Offer next batch if all batches complete
  ✓ Re-detects tools silently, reports new connections

2.5 Auto-Continue + Anti-Patterns

  ✓ Auto-continues to /profile after foundation built
  ✓ Does NOT show "→ /profile" as a manual command
  ✓ Never presents skills as a menu
  ✓ Never gates output on missing files
  ✓ Never asks more than 2 questions

---

Test Suite 3: /profile

  ✓ Reads company.md and icp.md
  ✓ Standalone if company.md missing
  ✓ 5-8 direct competitors researched
  ✓ 3-5 adjacent competitors researched
  ✓ White space analysis (what nobody else claims)
  ✓ Saturated claims (3+ competitors)
  ✓ ICP refinements proposed (buyer situation, positioning, disqualifiers)
  ✓ APPROVAL GATE before updating icp.md
  ✓ Auto-continues to /signal-scout after approval

---

Test Suite 4: /signal-scout

4.1 Signal Categories

All categories + proven tier:
  ✓ Proven signals (from won deals in icp.md) — shown FIRST
  ✓ Transactional (funding, M&A, hires, expansion — standard)
  ✓ Behavioral (buyer posting about problems, asking for recs,
    commenting on content, engaging with competitors) — highest value
  ✓ Negative (churned off vendor, employee turnover, declining
    metrics, Glassdoor reviews, spam database) — strongest triggers
  ✓ Organizational (reorg, IC→manager, downsized adjacent team)
  ✓ Competitive/Market (competitor raised, category crowded)
  ✓ Proxy (conferences, evaluating related tools)
  ✓ Buyer's Customer Signals (what's happening to THEIR customers)
  ✓ Social Signals (Reddit, X/Twitter, LinkedIn)
  ✓ Anti-Signals (disqualification patterns — shown in presentation)

  ✓ Explicit instruction: "Go deeper than 'company is hiring'"
  ✓ Behavioral + negative prioritized over transactional

Won deal integration:
  ✓ Checks icp.md for Won Deal Patterns section
  ✓ Extracts signals from real deals
  ✓ Labels proven vs theoretical signals
  ✓ Proven signals go to highest tier

Lost deal integration:
  ✓ Checks icp.md for Lost Deal Anti-Signals section
  ✓ Extracts anti-signals from lost deals
  ✓ Supplements with research-based anti-signals
  ✓ Anti-signals saved to signals.md for /prospect to use
  ✓ Competitor list built and saved to signals.md

Signal reliability hierarchy:
  ✓ Explicit ranking: job listings > proven > behavioral >
    negative > compliance > tech stack > website > transactional
  ✓ Saved to signals.md for /prospect scoring
  ✓ Website signals flagged as unreliable for back-office tools

Signal interpretation rules:
  ✓ Seller vs buyer distinction documented
  ✓ Source context matters (product page vs careers vs blog)
  ✓ Tech stack positive vs inverse correlation
  ✓ n=1 signal flagging requirement
  ✓ CRM confirmation bias warning (catalyst notes, MEDDPICC, etc.)

4.2 Social Signals

  ✓ Reddit: thread types + site:reddit.com queries
  ✓ X/Twitter: post types + site:twitter.com queries
  ✓ LinkedIn: engagement mining + site:linkedin.com/posts queries
  ✓ All use site: operators (no API keys)
  ✓ Explains why social = high-intent

4.3 Output + Flow

  ✓ Presentation: Proven / High-Intent / Moderate / Customer / Social
    + Anti-Signals + Signal Reliability Hierarchy
  ✓ Each signal: type, real example, why it matters, working query
  ✓ Anti-signals shown with ✗ prefix and disqualification reason
  ✓ Signal reliability hierarchy shown (1-8 ranking)
  ✓ Validates findability via WebSearch
  ✓ APPROVAL GATE
  ✓ Saves signals.md with: company + social search queries,
    anti-signals section, competitor list, reliability hierarchy
  ✓ Auto-continues to /prospect after approval
  ✓ Single-company mode when user names a company

---

Test Suite 5: /prospect

5.1 Search Channels

  ✓ Channel 1: Behavioral + Negative signals (HIGHEST priority)
    - LinkedIn posts, G2/Glassdoor reviews, churn events, turnover
  ✓ Channel 2: Social community mining (Reddit, X, LinkedIn threads)
  ✓ Channel 3: Company event signals (org changes, funding, hires)
  ✓ Channel 4: Proxy + content signals (conferences, blog, eval)
  ✓ Explicit: "Don't default to job boards"
  ✓ Channel reliability: Reddit > LinkedIn > X
  ✓ Guidance to skip X if thin results
  ✓ Captures SPECIFIC behavioral events, not generic "hiring SDRs"

Channel ordering (NEW v4.2 — hard rule):
  ✓ Skill mandates ≥2 Channel 1 searches BEFORE Channel 3/4
  ✓ Skill mandates ≥2 Channel 2 searches BEFORE Channel 3/4
  ✓ Explicit execution checklist in the skill
  ✓ Thin Channel 1/2 results must be noted, not hidden

5.2 Filtering + Anti-Signal Disqualification

  ✓ Checks Do Not Contact list from icp.md
  ✓ Within-run dedup across channels (merge same company)
  ✓ Cross-run dedup against prospects.md
  ✓ Excludes user's company + competitors from signals.md
  ✓ Checks disqualifier list from icp.md

Anti-signal checks (NEW):
  ✓ Loads anti-signals from signals.md
  ✓ Checks every company against anti-signal list
  ✓ 2+ anti-signal matches = auto-drop (moved to Dropped)
  ✓ 1 anti-signal match = -3 penalty + flag in output
  ✓ Competitor list from signals.md auto-excluded

Competitor vs buyer interpretation (NEW):
  ✓ Website signals checked: does company SELL or NEED the product?
  ✓ Product/features page = seller signal (competitor, not buyer)
  ✓ Careers/jobs page = buyer signal (high intent)
  ✓ Failed interpretation = -4 penalty or drop
  ✓ Flagged section in output for companies with single anti-signal

5.3 Scoring

  ✓ Fit Score: title +2, industry +2, size +2, not disqualified +1
  ✓ Behavioral signals: +4 (buyer posted about problem, asked for recs,
    churned off competitor, asking in community)
  ✓ Standard signals: high-30d +3, high-90d +2, moderate +1
  ✓ Bonuses: multiple signals +1, social-sourced +2, customer signal +1,
    job listing signal +1
  ✓ Combined max: ~18 with multiple behavioral signals
  ✓ Thresholds: Top 10+, Worth a Look 6-9, Dropped below 6
  ✓ Behavioral scores highest because buyer is actively thinking about problem

Anti-signal penalties (NEW):
  ✓ Single anti-signal match: -3 (flagged in output)
  ✓ Two+ anti-signal matches: auto-drop
  ✓ Competitor list match: auto-drop
  ✓ Failed seller-vs-buyer interpretation: -4
  ✓ Signal reliability weighting documented (job listings > website)

5.4 Contact + Email Enrichment

  ✓ One contact per company
  ✓ Title-case names, drop 1-char or initials
  ✓ LinkedIn URL captured

Tool-agnostic enrichment:
  ✓ Uses whatever enrichment tools are connected (no preference)
  ✓ Does NOT hardcode tool preferences or tiers
  ✓ API calls use environment variables, NEVER hardcoded
  ✓ Falls back gracefully per company if a tool fails

Pattern-guess fallback (when no enrichment tools):
  ✓ Checks for publicly available emails first
  ✓ Detects company email pattern from known employee emails
  ✓ Applies pattern to contact name (first.last@domain etc.)
  ✓ Marks pattern-guess emails as "pattern-guess — verify before sending"
  ✓ If no pattern detectable, marks as "LinkedIn only"
  ✓ NEVER leaves a prospect in a dead end — always has a next step

Email status in prospects.md:
  ✓ Verified email (from tool or public source)
  ✓ Pattern-guess email (with verification note)
  ✓ "LinkedIn only" (connection request instead)
  ✓ Email source column tracks where email came from

Fallback tool detection:
  ✓ If Connected Tools empty/missing in icp.md, /prospect detects
    tools independently (MCP check + env var check)
  ✓ Mid-session tool changes handled (re-detect and switch)
  ✓ ICP changes mid-flow handled (update and re-search)
  ✓ Loaded context display shows enrichment method being used

5.5 Approval + Flow

  ✓ APPROVAL GATE after company list
  ✓ APPROVAL GATE after contact list
  ✓ Auto-continues to /outreach after final approval
  ✓ Handles user-provided lists
  ✓ Handles "not enough results"
  ✓ Handles social-sourced unknown-company prospects

---

Test Suite 6: /outreach

6.1 Channel Selection

  ✓ Asks channel before writing: email / LinkedIn / both
  ✓ Accepts inline: "/outreach email", "/outreach linkedin", "/outreach both"
  ✓ Defaults to "both" if unspecified
  ✓ Description triggers include LinkedIn terms

6.2 Cold Email Framework

  ✓ 4 paragraphs + CTA, under 120 words
  ✓ Subject: lowercase, 2-4 words
  ✓ 5 opener types: observation, signal, question, buyer, social
  ✓ Social-sourced: references topic, NOT "I saw your post"
  ✓ Rotation across batch

6.3 Bridge Variation (NEW)

  ✓ 7 bridge angles documented:
    methodology, scale, accuracy, API, price, workflow, skip
  ✓ "Use 4+ different angles per 10 emails" rule
  ✓ "No single angle more than 3 times" rule
  ✓ "If you catch yourself writing the same sentence" warning

6.4 CTA Variation (NEW)

  ✓ 7+ CTA options documented
  ✓ "No CTA more than 3 times" rule
  ✓ CTA-opener pairing guidance
  ✓ "No CTA" option for senior execs

6.5 LinkedIn Framework (NEW)

  ✓ Under 300 characters (with COUNT instruction)
  ✓ 4 opener patterns: signal curiosity, market observation,
    buyer-world, mutual context
  ✓ 3+ non-obvious signals
  ✓ No pitch, no "I build...", no em dashes
  ✓ Never names a social platform as signal source (no "r/subreddit",
    no "on Twitter") — reference the TOPIC, not WHERE discussed
  ✓ Rotation across batch
  ✓ NOT a compressed version of the email
  ✓ When both channels: completely different signals (not just
    different framing of same signal)
  ✓ Handles "LinkedIn only" prospects (no email available)

6.6 Variation Plan (NEW — v4.1)

  ✓ Variation plan table created BEFORE writing any email
  ✓ Plan assigns: opener, bridge, CTA, client reference per prospect
  ✓ Batches of 5+: no type used more than 3x, 4+ bridge angles at 8+
  ✓ Batches under 5: each prospect gets different angles (relaxed caps)
  ✓ No two adjacent emails share same opener+bridge combo
  ✓ No client reference/case study used more than 3x

6.7 Output Format (v4.1)

  ✓ Every email has a subject line (lowercase, 2-4 words)
  ✓ Every email shows metadata: Signal | Opener | Bridge | CTA
  ✓ Word count shown for emails, char count for LinkedIn

6.7.5 Pre-Send Validator (NEW — v4.2)

Skill has a Step 4.5 "Pre-Send Validator — HARD CHECKS" block that
enumerates the hard fails the model must check before presenting:

Per email:
  ✓ Subject ≤4 words (with explicit failure example)
  ✓ Body <120 words
  ✓ Zero em dashes (grep the text for —)
  ✓ No banned vocabulary
  ✓ No hedging / exclamation / "I help" / tool names
  ✓ Company-name removal test

Per LinkedIn:
  ✓ <300 chars
  ✓ Zero em dashes
  ✓ NO product name (own product cannot appear in LinkedIn text)
  ✓ 3+ non-obvious signals
  ✓ Different signal than paired email
  ✓ No shared client ref with paired email

Per batch:
  ✓ Hard caps enforced (3x opener/bridge/CTA/ref)
  ✓ 4+ bridge angles at N=8+
  ✓ No adjacent opener+bridge duplicate
  ✓ LinkedIn independence test

Skill mandates: "Do not present a batch with known failures."

6.8 Batch Tests

  ✓ Opener test: all different across batch
  ✓ Bridge test: same sentence in 4+ = fail
  ✓ CTA test: same CTA in 4+ = fail
  ✓ Proof point test: same stat in 4+ = fail
  ✓ Reference test: same client ref in 4+ = fail (NEW v4.1)
  ✓ Template test: two prospects comparing = no template visible
  ✓ Cross-channel test: LinkedIn ≠ compressed email

6.9 Banned Vocabulary

  ✓ Full list: leverage, synergy, optimize, AI-powered, seamless,
    robust, unlock, empower, cutting-edge, revolutionary, transform,
    game-changer, furthermore, moreover, additionally, pivotal,
    crucial, testament, landscape, nestled, groundbreaking, renowned
  ✓ Tool names in output: Clay, Claude Code, Instantly, HeyReach
  ✓ Hedging: "I think", "maybe", "potentially"
  ✓ No exclamation points, no "I help", no em dashes

6.10 Humanizer Pass

  ✓ Structural: em dashes, rule of three, same structure, same length
  ✓ Vocabulary: banned list, copula avoidance, -ing analyses,
    vague attributions, promotional, filler
  ✓ Voice: match voice.md, vary across batch, anti-AI final pass
  ✓ NOT mentioned to user

6.11 Self-Improvement Loop

learnings.md tracking — 7 dimensions per send:
  ✓ Channel (email / linkedin / both)
  ✓ Signal type (proven / high-intent / moderate / social)
  ✓ Opener type
  ✓ Bridge angle
  ✓ CTA type
  ✓ Reply (yes / no / pending)
  ✓ Notes

Adaptation rules:
  ✓ Signal type with 2+ replies → promote to high-confidence
  ✓ Signal type with 0/5+ → deprioritize
  ✓ Opener type with replies → use more (still rotate)
  ✓ 3+ same opener type no replies → try others
  ✓ Bridge angle tracking + adjustment
  ✓ CTA tracking + adjustment
  ✓ Channel comparison (email vs LinkedIn rates)

Progressive refinement:
  ✓ Batch 1: baseline
  ✓ Batch 2-3: weight toward winners
  ✓ Batch 4+: pattern recommendations shown to user

Shows LEARNINGS APPLIED summary before writing:
  ✓ Batches sent, reply rates per channel
  ✓ Best signal/opener/bridge/CTA
  ✓ Adjustments being made

6.12 Presentation + Flow

  ✓ Email-only format with signal + opener + bridge metadata
  ✓ LinkedIn-only format with char count + pattern
  ✓ Both-channel format: side by side per prospect
  ✓ APPROVAL GATE with fix/cut/approve options
  ✓ Auto-continues to /push after approval

---

Test Suite 7: /push

7.1 Direct Push (Connected Tools)

  ✓ Checks Connected Tools from icp.md before offering file export
  ✓ Instantly API: creates campaign + adds leads directly
    - Uses $INSTANTLY_API_KEY (NEVER hardcoded)
    - Shows confirmation with campaign name
  ✓ Clay MCP: pushes contacts to Clay table
    - Uses track-event or add-contact-data-points
  ✓ Falls back to file export if no direct push tools
  ✓ Always offers file export as alternative even when tools connected

7.2 Export Formats

Email formats:
  ✓ Plain text (.txt)
  ✓ CSV (Instantly, Apollo, Smartlead)
  ✓ Outreach/Salesloft format
  ✓ HubSpot sequences format

LinkedIn formats:
  ✓ Copy-paste .txt (all messages with char counts)
  ✓ CSV for LinkedIn tools (HeyReach, Dripify)
  ✓ "Both email + LinkedIn" export option

  ✓ Auto-detects format from stack/tools in icp.md
  ✓ Falls back to asking if unknown
  ✓ Exports to ./gtm/export/

7.3 Email Status Handling

  ✓ Shows email status breakdown (verified / pattern-guess / LinkedIn only)
  ✓ Pattern-guess emails flagged "verify before sending"
  ✓ Offers to verify with connected tool (generic, no hardcoded preference)
  ✓ If no enrichment tools, suggests user connect one (no specific rec)
  ✓ Does NOT hardcode recommendations for specific tools
  ✓ LinkedIn-only contacts get connection requests (not a dead end)

7.4 Deliverability

  ✓ SPF/DKIM/DMARC mentioned
  ✓ Warmup guidance
  ✓ 50/day per mailbox limit
  ✓ Spread across days

7.5 Structured Result Logging

  ✓ Shows sent prospect list with numbers for easy marking
  ✓ Accepts flexible input ("1 and 4 replied", "nobody replied",
    "got a reply from {name}", etc.)
  ✓ Marks unmarked prospects as no-reply after user reports
  ✓ Asks for details on what they said (optional, helps learning)

7.6 Post-Send Feedback

learnings.md format captures:
  ✓ Summary: emails sent, replies, LinkedIn sent, accepts, rates
  ✓ Per reply: channel, signal type, opener, bridge, CTA, notes
  ✓ Per no-reply: same dimensions tracked
  ✓ Patterns section: signal, opener, bridge, CTA, channel, title
  ✓ Cumulative stats updated across all batches
  ✓ Best/worst performing combinations identified

Shows LEARNING UPDATE after logging:
  ✓ Reply rate this batch + cumulative
  ✓ WHAT'S WORKING section (winning patterns with rates)
  ✓ WHAT'S NOT section (anti-patterns to deprioritize)
  ✓ BATCH PROGRESSION (trend across all batches)

7.7 Next Batch Flow

  ✓ After logging results, offers "go" to start next batch
  ✓ Auto-continues to /prospect (dedupes against existing)
  ✓ /prospect uses updated learnings for signal prioritization
  ✓ /outreach uses updated learnings for pattern weighting
  ✓ The loop: send → log → learn → find → write → send

---

Test Suite 8: Simulated Output Grading

8.1 Mock Scenario

Company: BNBCalc (bnbcalc.com)
ICP: DSCR lenders, 50-500 emp, VP/Director level
Voice: Casual-professional, direct. Name: Julien.
Stack: HubSpot, Instantly, Apollo, LinkedIn manual
Connected Tools: Apollo API (email enrichment), Instantly API (direct push)

Won deals:
- Lima One: VP Lending, triggered by 40% projection miss,
  closed on 5-deal comparison (8% vs 35% variance)
- Visio: Dir Credit Risk, triggered by board risk mandate,
  closed on 2-week API pilot

Lost deals:
- PropTech startup: Head of Product, didn't buy because they
  built their own model. Anti-signal: company had "rental analytics"
  on their product page (competitor, not buyer)
- Consumer fintech: VP Ops, no B2B lending vertical.
  Anti-signal: consumer mortgage company, not DSCR lender

Target: Wade Susini, Chief Lender, Dominion Financial
Signals:
- News: #3 Scotsman, 82% headcount growth, wholesale launch
- LinkedIn: Partner posting about DSCR defaults (Mar 2026)
- Reddit: r/realestateinvesting thread on STR income projections

Channel: Both (email + LinkedIn)

8.2 Cold Email Rubric (/100)

Dimension	Weight	Criteria
Word count	10	Under 120 = full. 121-130 = half. Over 130 = 0.
Personalization	20	Names Dominion's product AND their borrower's situation. Remove-company-name test fails.
Signal integration	15	Weaves signal naturally as timing. Not listed as fact.
Voice match	15	Matches casual-professional. No banned words. No em dashes.
Bridge quality	15	Uses a SPECIFIC angle (not generic). Different from other emails in batch.
CTA quality	10	Specific, varies from other emails. Matches opener energy.
Structure	10	Subject lowercase. 3-4 paragraphs. Sign-off matches voice.
Social awareness	5	If social-sourced: topic reference, not "I saw your post."

8.3 LinkedIn Rubric (/100) (NEW)

Dimension	Weight	Criteria
Character count	20	Under 300 = full. 301-320 = half. Over 320 = 0.
Signal specificity	25	3+ signals, non-obvious, researched. Not "hiring" or "growing."
No pitch	20	Zero self-promotion. No product name. No "I build/run."
Tone	15	Curious peer, not vendor. Reads like someone in the same industry.
Differentiation	10	NOT a compressed version of the email. Different conversation.
Format	10	Correct structure. No em dashes. Ends with question/curiosity.

8.4 Batch Variation Rubric (/100) (EXPANDED)

Simulate 5 outreach pieces (email + LinkedIn each) and grade the SET:

Dimension	Weight	Criteria
Opener variety	20	All 5 emails use different openers. All 5 LinkedIn use different patterns.
Bridge variety	20	4+ different bridge angles across 5 emails. No sentence repeated.
CTA variety	15	3+ different CTAs. No CTA used more than twice.
Proof point variety	10	Same stat max 2 times. Different proof angles used.
LinkedIn independence	15	Each LinkedIn message is a different conversation from its paired email.
Voice consistency	20	All 10 pieces sound like the same person despite structural variety.

8.5 Self-Improvement Rubric (/100) (NEW)

Simulate: Batch 1 sent (5 emails, 5 LinkedIn). Got 2 email replies (signal leads with accuracy bridge), 1 LinkedIn accept (market observation). Grade how Batch 2 adapts.

Dimension	Weight	Criteria
Logging completeness	25	All 7 dimensions captured per send. Patterns section filled.
Signal adjustment	20	Winning signal types weighted higher in Batch 2.
Opener adjustment	20	Signal lead used more often (but still rotated).
Bridge adjustment	15	Accuracy bridge used more (but capped at 3). Losing angles reduced.
Learning summary shown	10	LEARNINGS APPLIED block shown before Batch 2 with rates + adjustments.
Not over-fitted	10	Still rotates. Doesn't abandon all non-winning patterns after 1 batch.

All rubric thresholds:

• 85+ = Ship it
• 70-84 = Minor fixes
• 50-69 = Rewrite needed
• Below 50 = Skill revision needed

---

Reporting

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  SIGNAL OUTBOUND KIT v4 — EVAL REPORT
  {date}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  STRUCTURE                    {pass}/{total}
  ├── Directory layout         {✓/✗}
  ├── Frontmatter              {✓/✗}
  ├── No leaked secrets        {✓/✗}
  ├── README quality           {✓/✗}
  └── Cross-skill consistency  {✓/✗}

  /start                       {pass}/{total}
  ├── Onboarding questions     {✓/✗}
  ├── Tool detection           {✓/✗}
  ├── Files created            {✓/✗}
  ├── Returning mode           {✓/✗}
  └── Auto-continue            {✓/✗}

  /profile                     {pass}/{total}

  /signal-scout                {pass}/{total}
  ├── Signal categories        {✓/✗}
  ├── Social signals           {✓/✗}
  ├── Won deal integration     {✓/✗}
  ├── Lost deal anti-signals   {✓/✗}
  ├── Signal reliability       {✓/✗}
  └── Interpretation rules     {✓/✗}

  /prospect                    {pass}/{total}
  ├── Search channels          {✓/✗}
  ├── Filtering + anti-signals {✓/✗}
  ├── Scoring + penalties      {✓/✗}
  ├── Email enrichment         {✓/✗}
  └── Approval + flow          {✓/✗}

  /outreach                    {pass}/{total}
  ├── Channel selection        {✓/✗}
  ├── Email framework          {✓/✗}
  ├── Bridge variation         {✓/✗}
  ├── CTA variation            {✓/✗}
  ├── LinkedIn framework       {✓/✗}
  ├── Batch tests              {✓/✗}
  ├── Banned vocabulary        {✓/✗}
  ├── Humanizer                {✓/✗}
  ├── Self-improvement loop    {✓/✗}
  └── Presentation + flow      {✓/✗}

  /push                        {pass}/{total}
  ├── Direct push (tools)      {✓/✗}
  ├── Email export formats     {✓/✗}
  ├── LinkedIn export formats  {✓/✗}
  ├── Missing email handling   {✓/✗}
  ├── Deliverability           {✓/✗}
  ├── Structured result log    {✓/✗}
  ├── Post-send feedback       {✓/✗}
  └── Next batch flow          {✓/✗}

  SIMULATED OUTPUT
  ├── Cold email               {score}/100
  ├── LinkedIn                 {score}/100
  ├── Batch variation          {score}/100
  └── Self-improvement         {score}/100

  ──────────────────────────────────────────────

  OVERALL: {passed}/{total} deterministic
  + {avg}/100 simulated output

  {SHIP IT | FIXES NEEDED | REWRITE}

  ──────────────────────────────────────────────

  FAILURES:

  [{suite}.{test}] {what failed}
    Expected: {what should happen}
    Found: {what was found}
    File: {path}:{line}
    Fix: {specific actionable fix}

---

Adding New Tests

Every manual fix = a new test case. The eval grows with the kit.