nimbleway/agent-skills/market-finder
Claude Code and agent skill by nimbleway/agent-skills
- community
Checking that the SKILL.md file is still in the repository.
Discovers all businesses of a given type in any geography using Nimble WSAs. Two modes: Discovery finds businesses from scratch; Audit compares a user's existing list (Google Sheet, CSV, inline) against fresh discovery, categorizing entries as matched, discovered-only, or reference-only. Vertical presets (Healthcare, SaaS, Restaurants, Legal, Auto/Home) auto-select WSA routing. Triggers: "find all X in Y", "build a list of", "market sizing", "account universe", "how many X in Y", "TAM for", "discover all", "audit my list", "compare against", "what am I missing", "gap analysis", "verify my business list", "prospect list". Do NOT use for competitor monitoring — use competitor-intel instead. Do NOT use for company deep dives — use company-deep-dive instead. Do NOT use for neighborhood-level exploration with social enrichment — use local-places instead.
Install
npx vskill@latest install nimbleway/agent-skills/market-finderSKILL.md
Market Finder
Market intelligence powered by Nimble Web Search Agents.
User request: $ARGUMENTS
Before running any commands, read references/nimble-playbook.md for Claude Code constraints (no shell state, no &/wait, sub-agent permissions, communication style).
Instructions
Step 0: Preflight
Follow the transport selection + standard preflight from references/nimble-playbook.md — pick CLI or MCP at session start, then run the standard preflight calls (date calc, today, profile, memory index) in parallel.
Also simultaneously:
mkdir -p ~/.nimble/memory/{reports,market-finder/checkpoints}- Check for existing checkpoints:
ls ~/.nimble/memory/market-finder/checkpoints/ 2>/dev/null
From the results:
- CLI missing or API key unset ->
references/profile-and-onboarding.md, stop - Tag all
nimbleCLI calls:nimble --client-source nimble-agent-skills <subcommand>. MCP requests are attributed at the transport level — seereferences/nimble-playbook.md. - Profile exists -> note industry keywords if any. Apply smart date windowing from
references/nimble-playbook.md. Market-finder tweak: in quick refresh mode, skip enrichment and only discover new metros.
- No profile -> fine. Market-finder doesn't require onboarding. Proceed to Step 1.
Step 1: Parse Request & Detect Mode
Parse $ARGUMENTS for business type, geography, qualifiers, and mode detection.
Mode detection
Check $ARGUMENTS for a reference list. Read references/audit-mode.md for the full detection signals and parsing rules.
| Signal | Mode | |
|---|---|---|
| Google Sheet URL, CSV path, or inline list of 3+ businesses | Audit | |
| Explicit audit language ("audit my list", "compare against", "gap analysis") | Audit | |
| No reference list provided | Discovery (default) |
If a reference list is present but intent is ambiguous, ask: "Want me to audit your list against fresh discovery, or use it as a starting point?"
If audit language is detected but no reference list is provided, ask: "You mentioned auditing — please provide your list (Google Sheet URL, CSV file path, or paste inline)." Do not proceed with Audit mode until a reference list is received.
Extract fields
| Field | Required | Source | |
|---|---|---|---|
| Business type / vertical | Yes | User input ("dentists", "SaaS CRM tools") | |
| Geography | Yes (except SaaS) | User input ("Florida", "Austin TX", "nationwide") | |
| Reference list | Audit mode only | Google Sheet URL, CSV path, or inline | |
| Qualification criteria | Optional | User input ("must have website", "10+ reviews") | |
| Output preference | Optional | User input ("quick summary", "full dataset") |
If both type and geography are clear from $ARGUMENTS, confirm briefly and proceed: "Finding dentists in Florida..." (or "Auditing your list against dentists in Florida..." in Audit mode)
If partial or ambiguous, ask one combined question (counts as 1 of max 2 AskUserQuestion prompts):
Use AskUserQuestion with up to 3 questions:
- Vertical -- "What type of business?" with options: Healthcare, SaaS/Software,
Restaurants/Food, Legal/Financial, Auto/Home Services, Other
- Geography -- "What geography?" (free text or: City, State, Region, Nationwide)
- Depth -- "Quick scan or comprehensive discovery?"
Skip questions already answered by $ARGUMENTS.
Depth modes (determines how much work each step does):
| Depth | Discovery | Enrichment | Verification | Distribution | |
|---|---|---|---|---|---|
| Quick scan | All sources, 1 pass | Skip (or top 5 only) | Top 5 entities | Offer | |
| Comprehensive | All sources + fallback retries | Full | All entities | Offer |
Step 2: Vertical Detection & Preset Loading
Read references/vertical-presets.md and match the user's business type against preset trigger keywords.
| Match | Action | |
|---|---|---|
| Clear match | Load that preset's WSA routing and query pattern | |
| Partial match | Confirm: "This looks like Healthcare. Use healthcare presets?" | |
| No match | Use Custom preset with user's keywords | |
| SaaS match | Switch to non-geographic pipeline (no geo-tiling) |
Note which discovery WSAs and enrichment WSAs the preset specifies.
Step 3: Geographic Scoping
Skip this step for SaaS vertical (no geography needed).
| Geography level | Tiling strategy | |
|---|---|---|
| City | Single query, no tiling | |
| Metro area | Single query per WSA | |
| State | Tile by top 5-10 metros in the state | |
| Region | Tile by states, then top metros per state | |
| Nationwide | Tile by all states, then top metros per state |
Estimate API calls: metros * discovery_wsas * (1 + enrichment_ratio) where enrichment_ratio is ~0.3. Follow the Scaled Execution pattern from references/nimble-playbook.md to choose execution tier (individual / batch / multi-batch / confirmation gate):
Derive a slug for checkpointing: lowercase, hyphenated, includes vertical + geo (e.g., dentists-florida, saas-crm-tools, hvac-nationwide).
Step 4: Check for Existing Checkpoint
Follow the Checkpointing & Resume pattern from references/memory-and-distribution.md.
Check: cat ~/.nimble/memory/market-finder/checkpoints/{slug}/discovery.json 2>/dev/null
- Checkpoint found -> offer: "Found previous run ({N} entities from {date}).
Resume and fill gaps, or start fresh?"
- No checkpoint -> proceed to Step 5
Step 5: WSA Discovery & Execution
5a: Discover available WSAs
For each target domain in the selected vertical preset, discover current WSAs:
Run these searches simultaneously (one per target domain). From the results:
- Filter by entity_type (SERP for discovery, PDP/Profile for enrichment)
- Prefer
managed_by: "nimble"overmanaged_by: "community" - If no WSA found for a domain, mark it for
nimble searchfallback - If no WSAs found for ANY domain, fall back entirely to
nimble searchfor all metros
Then validate each discovered WSA's input params:
Cache the discovered WSA names + params for the rest of the run.
5b: Geographic discovery (all except SaaS)
For each metro in the tiling plan, run the discovered WSAs simultaneously:
Run tertiary domain WSAs only if the preset includes them AND primary + secondary return < 10 combined unique results for that metro.
Choose execution tier per the Scaled Execution pattern in references/nimble-playbook.md (based on total estimated calls from Step 3).
5c: SaaS discovery (non-geographic)
SaaS skips WSA discovery. Run the two-pass search queries defined in the SaaS preset from references/vertical-presets.md:
- Pass 1 -- Product discovery: G2, Capterra, general, ProductHunt, GitHub
- Pass 2 -- Financial discovery: Crunchbase, funding news, market landscape
Both passes run simultaneously. Pass 2 is critical -- without it, funding and traction data will be missing or wrong.
5d: Fallback
If no WSA was found for a target domain, or if a WSA fails for any metro:
After discovery:
- Parse all results into a unified entity list
- Deduplicate following the Entity Deduplication pattern from
references/nimble-playbook.md: place_id -> domain -> fuzzy name + city
- Track
source_countper entity (how many WSAs/sources found it) - Save checkpoint:
~/.nimble/memory/market-finder/checkpoints/{slug}/discovery.json
Step 6: Enrichment
Run enrichment using the WSAs discovered in Step 5a for the preset's enrichment target domains. Prioritize entities with the highest source count first. Choose execution tier per Scaled Execution in references/nimble-playbook.md.
Only run enrichment WSAs that apply to the current vertical's enrichment targets (see references/vertical-presets.md). Skip entities without the required ID/URL for the enrichment WSA.
Save checkpoint: ~/.nimble/memory/market-finder/checkpoints/{slug}/enrichment.json
Step 6b: Financial Verification (SaaS vertical)
For SaaS entities, verify funding claims before reporting. Never label a company's funding stage without a source.
For each entity in the top results (top 5 in quick scan, all in comprehensive):
- Source found: Use the sourced amount and date
- No source found: Display "Undisclosed" -- never guess "Early stage" or "Bootstrapped"
This step prevents publishing unverified financial claims. It's fast (one search per entity, lite depth) and catches recent funding rounds that directory sites miss.
Step 7: Deduplication & Scoring
Final deduplication: Run a final dedup pass across all phases following the Entity Deduplication pattern from references/nimble-playbook.md. Merge fields from multiple sources into a single record per entity.
Discovery strength scoring (skill-specific, varies by vertical):
Geographic verticals (Healthcare, Restaurants, Legal, Auto/Home, Custom):
| Level | Criteria | |
|---|---|---|
| High | 3+ sources OR 2+ sources with reviews > 50 | |
| Medium | 2 sources OR 1 source with reviews > 10 | |
| Low | 1 source only, few/no reviews |
SaaS vertical (funding + directory presence matter more than review count):
| Level | Criteria | |
|---|---|---|
| High | Verified funding > $10M OR 3+ directory sources OR 1000+ G2 reviews | |
| Medium | Verified funding < $10M OR 2 sources OR 100+ G2 reviews | |
| Low | 1 source only, no verified funding, few reviews |
Display as: *** High, ** Medium, * Low
Step 7b: Audit Comparison (Audit mode only)
Skip this step in Discovery mode.
Read references/audit-mode.md for the full matching algorithm, normalization rules, and output template.
- Parse reference list — detect format (Google Sheet / CSV / inline), extract
records, normalize to {name, domain, city, state, phone} per the parsing rules in references/audit-mode.md
- Run three matching layers in order (domain → name+city → phone). Once an entity
matches at any layer, stop. Track which layer produced the match.
- Categorize every entity:
matched— in both reference list and discovery resultsdiscovered_only— found by discovery, not in reference listreference_only— in reference list, not found by discovery
- Calculate coverage score —
matched / reference_count × 100
Proceed to Step 8 with the categorized results.
Step 8: Output
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/market-finder/SKILL.md
Popularity
- Repository stars
- 50
- Repository forks
- 16
- 7-day trend score
- 20
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 7 Aug 2026, 3 months ago.
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