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 Snowflake-Labs/cocoplus --skill meter-estimategit clone --depth 1 https://github.com/Snowflake-Labs/cocoplusWrote 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/snowflake-labs/cocoplus/meter-estimate)<a href="https://agentmods.dev/skills/snowflake-labs/cocoplus/meter-estimate"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/meter-estimate.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00842 |
| Opus 5 | $0.00021 | $0.00421 |
| Sonnet 5 | $0.00008 | $0.00168 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
meter-estimate 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 4d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your objective is to estimate token and cost impact before executing an action.
Before proceeding, verify that .cocoplus/ exists.
If not: output "CocoPlus not initialized in this directory. Run $pod init to begin." Then stop.
If no argument provided: read .cocoplus/flow.json to estimate the full pipeline.
If argument provided (e.g., $meter estimate "run 3-stage pipeline"): estimate the described action.
Estimation Approach
For pipeline estimation:
- Count stages in flow.json
- For each stage, estimate based on persona and typical workload:
- data-engineer: ~8,000 tokens/stage (SQL-heavy)
- analytics-engineer: ~6,000 tokens/stage (semantic modeling)
- data-scientist: ~12,000 tokens/stage (notebook + analysis)
- data-analyst: ~4,000 tokens/stage (queries + reporting)
- bi-analyst: ~3,000 tokens/stage (visualization spec)
- data-product-manager: ~2,000 tokens/stage (documentation)
- data-steward: ~3,000 tokens/stage (governance)
- chief-data-officer: ~2,000 tokens/stage (review)
Apply Accuracy Learning Calibration
Read .cocoplus/meter/adjustment-factor.json if it exists:
{ "factor": N, "sample_size": N, "computed_at": "..." }
If the file exists and sample_size >= 2:
calibrated_total = raw_total × factor- Calibration label:
(baseline: [raw_total], calibration factor: [factor]x from [sample_size] prior sessions)Else: calibrated_total = raw_total- No calibration label
Write estimate to .cocoplus/meter/preflight-log.jsonl:
{ "session_id": "[current-session-id]", "estimated_tokens": [calibrated_total], "estimated_credits": [estimated_credits], "timestamp": "[ISO 8601]" }
Output:
# Pre-flight Estimate
Action: [described action or "Full pipeline execution"]
## Token Estimate
Per stage breakdown:
[stage name] ([persona]): ~[estimate] tokens
...
Baseline estimate: ~[raw_total] tokens
[If calibrated:] Calibrated estimate: ~[calibrated_total] tokens [calibration label]
[If not calibrated:] Total estimate: ~[raw_total] tokens (conservative — no calibration data yet)
## Snowflake Credit Estimate
Estimated SQL calls: ~[N]
Estimated credits: ~[N × 0.00001] credits
## Budget Check
Configured threshold: [from cost-tracker.monitor.json]
Estimate vs threshold: [WITHIN / EXCEEDS by N%]
Note: These are estimates. Actual usage depends on response length, query complexity, and data volume.
Run `$meter accuracy` to view calibration history.
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.
- 4d ago First seen · 91 lines · 42 tokens per session scan A 9ae8140d265e
meter-estimate is a skill published in the GitHub repository Snowflake-Labs/cocoplus (720 stars, last pushed 4d ago), licensed MIT. It adds 42 tokens to every session and 842 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 2026-09-03.
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