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 agentmods add skills/voxtechnologies/anty-framework/qualificationnpx skills add VoxTechnologies/anty-framework --skill qualificationgit clone --depth 1 https://github.com/VoxTechnologies/anty-frameworkWhat 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 | $0.00071 | $0.01024 |
| Opus 5 | $0.00036 | $0.00512 |
| Sonnet 5 | $0.00014 | $0.00205 |
| Haiku 4.5 | $0.00007 | $0.00102 |
Grade A, and why
qualification 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- qualification — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Qualification
When to Apply
- Evaluating new leads for pipeline entry
- Marketing-sales handoff decisions
- When pipeline quality is poor (low conversion rates)
- When downstream bottleneck exists (too many unqualified leads)
- Configuring qualification criteria during onboarding
Core Framework
BANT 6-Criteria Gate
Every lead must pass all 6 criteria before entering the pipeline at Step 2:
| Criteria | Question | Pass Condition |
|---|---|---|
| Problem | Does the prospect have a problem our product solves? | Specific, articulated pain point matching our solution |
| Budget | Is budget allocated or likely? | Budget exists or can be created within purchase timeline |
| Authority | Is the decision-maker engaged or accessible? | Direct contact with buyer, or champion with access to buyer |
| Timeline | Is there a reasonable purchase timeframe? | Active evaluation, not "maybe someday" |
| Fit | Does our product capability match their need? | Core use case alignment, not edge-case stretching |
| Margin | Can we achieve acceptable margin on this deal? | Deal economics above minimum threshold |
Qualification Flow
Incoming lead
|
+-> Score against 6 criteria
|
+-> All 6 pass: QUALIFIED
| -> Enter pipeline Step 2
| -> Assign to appropriate sales Actions
|
+-> 1-2 fail: NURTURE
| -> Add to nurture sequence
| -> Re-evaluate in 30/60/90 days
| -> Do NOT add to pipeline
|
+-> 3+ fail: DISQUALIFY
-> Remove from active tracking
-> Log reason for future pattern analysis
Downstream Bottleneck Rule
When the pipeline bottleneck is downstream (e.g., demo capacity at 90% utilization):
Reduce upstream lead gen volume, don't increase it.
Bottleneck: Demo capacity (30/month, 90% utilized)
Qualified leads waiting: 15 in queue
WRONG: "Generate more leads to increase pipeline"
RIGHT: "Reduce lead gen to match demo throughput.
Generating more leads than demo can handle is waste."
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.
- 2d ago First seen · 104 lines · 71 tokens per session scan A bf9004744347
qualification is a skill published in the GitHub repository VoxTechnologies/anty-framework (6 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 1,024 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
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Cash Machine 10-step B2B sales pipeline with 3 presets, verifiable checkpoints per step, trajectory logging, bottleneck detection with utilization formula, lead qualification gate (BANT 6-criteria), pipeline velocity and stall detection (2x threshold), two-tier probability scoring, BBS tracking, end-of-quarter…
anticipatory-selling
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content-rules
Content generation rules — customer-as-protagonist rewriting, inflated language filter, precision targeting, sell results not products, and anticipatory selling material generation for sales Steps 5-7. Use when generating any content, reviewing drafts, or creating sales support materials.
disruption
Disruption analysis using Innovator's Dilemma economics, cannibalization exposure, competitor response classification, market entry signals, and six-force environmental monitoring. Use when evaluating competitive landscape, entering markets with incumbents, or during periodic strategic scans.
network-effects
Andrew Chen's Cold Start Problem framework — atomic network definition with thresholds by product type, anti-peanut-buttering, zero tracking, escape velocity 3-force decomposition (engagement/acquisition/economic), growth ceiling 5-force detection, competitive position dynamics, T2D3 benchmark. Use for products with…
value-stick
Oberholzer-Gee's Value Stick — 4-layer model (Customer Delight, Firm Margin, Employee Satisfaction, Supplier Surplus), 3 diagnostic patterns (stick too short, delight giveaway, cost squeeze), "too expensive" reframe (WTP vs perception), WTS as strategic lever, complement profit pool analysis (WTP engine vs profit pool…