Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add softspark/ai-toolkit --skill biz-scangit clone --depth 1 https://github.com/softspark/ai-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/softspark/ai-toolkit/biz-scan)<a href="https://agentmods.dev/skills/softspark/ai-toolkit/biz-scan"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/biz-scan.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.01133 |
| Opus 5 | $0.00017 | $0.00566 |
| Sonnet 5 | $0.00007 | $0.00227 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
biz-scan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Biz Scan Command
$ARGUMENTS
Triggers the Business Intelligence agent to analyze the codebase for business opportunities and KPI gaps.
Usage
/biz-scan [scope]
# /biz-scan schema : focus on database models and entity relationships
# /biz-scan api : focus on API endpoints and data exposure
# /biz-scan all : full codebase scan
Protocol
1. Model Scan: Analyze Data Layer
Scan for business-relevant data structures:
# Find database models, schemas, entities
grep -rl "model\|schema\|entity\|migration" --include="*.py" --include="*.ts" --include="*.rb" .
# Find ORM definitions
grep -rl "prisma\|sequelize\|typeorm\|sqlalchemy\|activerecord" .
Catalog: entity names, relationships, fields that map to business concepts (revenue, subscription, usage, billing).
2. Logic Scan: Analyze Business Logic
Scan controllers, services, and use cases:
# Find API endpoints and handlers
grep -rn "router\.\|app\.\(get\|post\|put\|delete\)\|@Controller\|@app\.route" --include="*.ts" --include="*.py" --include="*.js" .
# Find tracking/analytics events
grep -rn "track\|analytics\|event\|metric\|log_event" --include="*.ts" --include="*.py" --include="*.js" .
Catalog: exposed endpoints, tracked events, feature flags, A/B tests.
3. Synthesis: Match Data vs. Business Goals
Cross-reference findings to identify:
| Category | What to Look For |
|---|---|
| Missing KPIs | Entities with no associated tracking events |
| Underutilized features | Endpoints with no analytics or feature-flag coverage |
| Monetization gaps | Subscription/billing entities without conversion tracking |
| Data exposure | Rich internal data not surfaced via API |
4. Report: Generate Opportunity Report
Output a structured markdown report:
## Business Opportunity Report: [scope]
### KPI Coverage
| Entity/Feature | Tracked Events | Gap |
|---------------|---------------|-----|
| [name] | [events or "none"] | [what's missing] |
### Opportunities (ranked by estimated impact)
1. **[Opportunity]**: [description, affected entities, suggested action]
### Quick Wins
- [ ] Add tracking to [feature], estimated lift: [low/med/high]
### Data Exposure Gaps
- [Entity] has [N fields] not exposed via any API endpoint
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 111 lines · 35 tokens per session scan A 4a3300a47221
biz-scan is a skill published in the GitHub repository softspark/ai-toolkit (170 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 1,133 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
cline-fix-volatile-msg
Ladder-aware Cline Anthropic caching — verify the rolling read/write ladder on the wire, then add the tools breakpoint and tune TTL. Updated for the 2026-08 AI-SDK monorepo.
continue-gemini-explicit
Continue's Gemini provider doesn't use the cachedContents API at all. Add explicit caching for sessions over the minimum token threshold.
aider-1h-ttl
Aider uses 5min TTL by default and works around long pauses with keepalive pings. Wire up the 1h TTL beta instead.
cline-openai-cache-key
Cline OpenAI native provider sends no promptcachekey. Add a stable per-task key so cachedtokens stops being zero.
continue-enable-defaults
Continue's prompt caching is opt-in via config and off by default. Flip the default to systemAndTools.
continue-fix-volatile-msg
Ladder-aware Continue Anthropic caching — verify the rolling ladder on the wire, then enable it by default and add TTL coverage.