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 winstonkoh87/Athena-Public --skill client-pricinggit clone --depth 1 https://github.com/winstonkoh87/Athena-PublicWrote 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/winstonkoh87/athena-public/client-pricing)<a href="https://agentmods.dev/skills/winstonkoh87/athena-public/client-pricing"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/client-pricing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/winstonkoh87/athena-public/client-pricing"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/client-pricing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 36 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00033 | $0.00998 |
| Opus 5 | $0.00016 | $0.00499 |
| Sonnet 5 | $0.00007 | $0.00200 |
| Haiku 4.5 | $0.00003 | $0.00100 |
Grade A, and why
client-pricing 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 10d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Client Pricing Skill
Purpose: Prevent rate collapse. Enforce anchor-first pricing. Automate the quoting decision tree. Origin: Empirical calibration from real client engagements — rate collapse incidents and floor-as-opening negotiation failures. Both were preventable.
Core Principle
"AI commoditizes labor. It cannot commoditize judgment."
Pricing Hierarchy (defensibility axis): Time (❌) → Output (❌) → Deliverable (⚠️) → Outcome (✅) → Access (✅✅)
Never price at the Time or Output layer. Price at Deliverable (minimum) or Outcome (preferred).
Tiered Pricing Table
| Deliverable Type | Anchor | Floor | Notes |
|---|---|---|---|
| Essay (1000–2000 words) | $250 | $150 | Counter at $200 if pushback |
| Problem Set (SPSS, coding, math) | $350 | $250 | Scope-dependent; +$50/additional test family |
| Capstone/Report (5000+ words) | $1,000 | $500 | Multi-round negotiation expected |
| Presentation (slides + script) | $300 | $200 | +$100 if design assets required |
| Speed Premium (< 48hr turnaround) | +30% | — | Non-negotiable surcharge |
| Complexity Premium (cross-domain) | +20% | — | E.g., engineering + writing + coding |
The Negotiation Decision Tree
YOU: State anchor price
↓
CLIENT: "Too high"
↓
YOU: "What's your budget?" (NEVER counter against yourself)
↓
CLIENT names their number
↓
├─ (A) Within 20% of anchor → Counter midpoint, settle ±10%
├─ (B) 40-60% of anchor → Counter at floor + 20%, settle at floor + 10%
├─ (C) Below floor → "Sorry, [floor] is the lowest I can go"
│ ├─ Client accepts → Done
│ └─ Client walks → Let them (Dignity Premium)
└─ (D) Client ghosts → Follow up once at 24hr. No chase after.
Three rounds maximum. After round 3, you're haggling, not negotiating.
Anti-Patterns (Reflexion Archive)
| Anti-Pattern | Case Study | Fix |
|---|---|---|
| Opening at floor | Quoted at floor instead of anchor — left $50+ on the table | Always open at anchor. Floor is your walk-away, not your opening |
| Rate collapse via speed | Delivered fast, effective rate dropped to $83/hr vs $310/hr benchmark | Price by deliverable complexity, not hours. Speed is your competitive advantage — don't let it compress price |
| Negotiating against yourself | Generic pattern | After stating anchor, SHUT UP. Let the client name their number |
| Scope creep without re-quote | Client adds "just one more thing" | Any addition > 10% of original scope triggers re-quote |
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.
- 10d ago First seen · 96 lines · 33 tokens per session scan A 3f26386911f7
client-pricing is a skill published in the GitHub repository winstonkoh87/Athena-Public (587 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 998 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.
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