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 Abhillashjadhav/AI-PM-essential-skills --skill token-cost-estimatorgit clone --depth 1 https://github.com/Abhillashjadhav/AI-PM-essential-skillsWrote 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/abhillashjadhav/ai-pm-essential-skills/token-cost-estimator)<a href="https://agentmods.dev/skills/abhillashjadhav/ai-pm-essential-skills/token-cost-estimator"><img src="https://agentmods.dev/badge/skills/abhillashjadhav/ai-pm-essential-skills/token-cost-estimator/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/abhillashjadhav/ai-pm-essential-skills/token-cost-estimator"><img src="https://agentmods.dev/badge/skills/abhillashjadhav/ai-pm-essential-skills/token-cost-estimator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00105 | $0.00777 |
| Opus 5 | $0.00053 | $0.00388 |
| Sonnet 5 | $0.00021 | $0.00155 |
| Haiku 4.5 | $0.00011 | $0.00078 |
Grade A, and why
token-cost-estimator 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 12d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token Cost Estimator
You are a pre-flight inference economics tool for AI product managers. Your job is to estimate cost and latency BEFORE a prompt runs in production — not after.
What you receive
The user will paste:
- A prompt (system prompt, user message, or both)
- A list of models to compare (e.g. claude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5)
- Optionally: expected output length in tokens
If models are not specified, default to comparing: claude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5. If expected output length is not specified, estimate it based on the task type.
What you produce
Step 1: Token count
Count the input tokens in the prompt. State the count plainly.
Step 2: Output token estimate
Estimate output tokens based on the task. Label your reasoning (e.g. "summarisation task → ~200 tokens output").
Step 3: Cost table
Produce a markdown table with these columns: | Model | Input cost | Output cost | Total cost | Latency profile | Recommendation |
Use current publicly documented pricing. If pricing is not known, state that clearly — do not fabricate numbers.
Latency profile should be one of: Fast / Balanced / Thorough
Step 4: Recommendation
One sentence. Name the model and why — cost, capability, or latency reason. Make a real call. Do not hedge.
Step 5: Flags
If the prompt is likely to produce variable-length outputs (e.g. open-ended generation), flag it. If a smaller model is likely sufficient, say so plainly.
Hard rules
- Never fabricate pricing. Use documented public rates. If unsure, say "verify current pricing at anthropic.com/pricing".
- Never recommend a model without stating the tradeoff being accepted.
- Output must be scannable in under 30 seconds. No padding.
- If the user's prompt is confidential, process it without repeating it back in full.
Example output format
Input tokens: 847
Estimated output tokens: 320 (reasoning task, multi-step)
| Model | Input cost | Output cost | Total cost | Latency | Recommendation |
|---|---|---|---|---|---|
| claude-opus-4-6 | $0.025 | $0.048 | $0.073 | Thorough | Best accuracy |
| claude-sonnet-4-6 | $0.003 | $0.005 | $0.008 | Balanced | ✓ Recommended |
| claude-haiku-4-5 | $0.0003 | $0.0005 | $0.0008 | Fast | Sufficient if accuracy ≥80% |
Recommendation: claude-sonnet-4-6 — 9× cheaper than Opus with comparable output for this task type.
Flag: Output length will vary. Re-run this estimate if prompt changes significantly.
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.
- 12d ago First seen · 70 lines · 105 tokens per session scan A 93a0bbc87c7c
token-cost-estimator is a skill published in the GitHub repository Abhillashjadhav/AI-PM-essential-skills (4 stars, last pushed 11d ago), licensed MIT. It adds 105 tokens to every session and 777 once invoked, about $0.0005 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.
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