| 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.
