version: "1.0.1" name: cost-tracking description: Use when the user wants to capture AI tool costs, review spending trends, set cost budgets, or integrate cost data into health snapshots — guides quarterly cost capture, records data in a structured format, and updates MODEL_ROUTING.md with observed cost patterns

Cost Tracking

Capture, record, and track AI tool costs over time. Cost data feeds into health snapshots and informs model routing decisions.

This skill does not access billing APIs directly — it guides the user through checking their provider dashboards and recording the data in a structured format that the plugin can read.

Why Track Costs

Without cost data:

• MODEL_ROUTING.md routing rules are theoretical
• The break-even calculation for self-hosting is impossible
• Cost per PR/feature is unknown — no way to optimise
• Budget conversations happen without evidence

With cost data:

• Routing rules are validated against actual spend
• Self-hosting decisions are grounded in real numbers
• Cost trends reveal whether AI adoption is efficient
• Budget conversations have receipts

Two actuals records: the quarterly snapshot and the per-PR record

This skill owns two actuals formats under observability/costs/:

• The quarterly snapshot (below) — a provider-level aggregate of spend and

tokens across all work for a billing period, captured by /cost-capture.

• The per-PR actuals record — a single-task structural footprint (which

stages ran, review cycles, files) plus human-supplied token/cost figures when available, written by the integration-agent at merge time and read by the cost-estimator as a kind: calibration source. It lives under observability/costs/per-pr/ and is defined in `references/per-pr-actuals-format.md`. The two never share a file or directory.

The Cost Snapshot

Cost data is captured in observability/costs/YYYY-MM-DD-costs.md. Each file records one capture session (typically quarterly).

Format

# Cost Snapshot — YYYY-MM-DD
 
## Provider Spend
 
| Provider | Period | Spend | Tokens (input) | Tokens (output) |
| --- | --- | --- | --- | --- |
| Anthropic | YYYY-MM to YYYY-MM | $X,XXX | XXM | XXM |
| OpenAI | YYYY-MM to YYYY-MM | $X,XXX | XXM | XXM |
 
## Model Breakdown (if available)
 
| Model | Tokens (input) | Tokens (output) | Estimated cost |
| --- | --- | --- | --- |
| claude-sonnet-4 | XXM | XXM | $XXX |
| claude-opus-4 | XXM | XXM | $XXX |
| claude-haiku-4 | XXM | XXM | $XXX |
 
## Per-Project Estimate
 
| Project/Repo | Estimated share | Rationale |
| --- | --- | --- |
| ai-literacy-superpowers | XX% | Primary development repo |
| ai-literacy-exemplar | XX% | Secondary, used for testing |
 
## Observations
 
-[Any patterns noticed — cost spikes, model tier shifts, etc.]
-Cost-estimate grounding: grounds | proxied (<absent tier(s)>) | omitted (no estimating-tier family) | omitted (no per-model breakdown)
 
## Budget Status
 
-Monthly budget: $X,XXX (or "not set")
-Current monthly average: $X,XXX
-Trend: increasing / stable / decreasing
-Action needed: yes / no

Estimating-tier coverage and the cost-estimation sibling

A captured snapshot's Model Breakdown coverage determines whether the prospective cost-estimation sibling can ground a dollar figure. The estimator binds its routing tiers to model families by stem (claude-opus-4 → Most capable, claude-sonnet-4 → Standard; see the cost-estimation binding table). So:

• a breakdown containing an opus-4 and a sonnet-4 family row grounds

estimates directly;

• a breakdown with only one of them grounds, but proxies the absent

tier (a disclosed over-estimate);

• a breakdown with neither (e.g. only a claude-haiku-4 row — a valid

breakdown entry, but Haiku is not an estimating tier) means estimates omit cost; and a snapshot with no Model Breakdown at all omits for a structural reason.

/cost-capture reports which of these applies at capture time and records it in the Cost-estimate grounding: Observations line above, so the gap is visible when a human can act on it — not discovered estimate-by-estimate.

Process

Step 1: Check Provider Dashboards

Guide the user to their billing pages:

Anthropic:

Check your usage at: https://console.anthropic.com/settings/billing
Look for: monthly spend, token usage by model, usage over time

OpenAI:

Check your usage at: https://platform.openai.com/usage
Look for: monthly spend, model breakdown, daily usage chart

Other providers: Ask the user where to find their billing data.

Step 2: Record the Data

Create observability/costs/YYYY-MM-DD-costs.md using the format above. Ask the user for each field:

1. Which providers are in use?
2. What was the spend for the period?
3. Can they break it down by model? (Not always available)
4. Which projects consumed the most? (Estimate if not precise)

Step 3: Compare to Previous Snapshot

If a previous cost snapshot exists in observability/costs/, read it and compute:

• Spend delta ($ and %)
• Token volume delta
• Model mix changes
• Cost per token trend

Step 4: Update MODEL_ROUTING.md

If the cost data reveals patterns that should change routing:

• High spend on frontier models for tasks that could use standard →

suggest updating the Agent Routing table

• Consistent use below the self-hosting break-even → note that

cloud is still optimal

• Spend above budget → flag which model tier is the driver

Update the Sovereignty Considerations section with observed data.

Step 5: Update Health Snapshot

The next /harness-health run will read the latest cost snapshot and populate the Cost Indicators section. The skill does not update the snapshot directly — it produces the cost data file that the snapshot reads.

Step 6: Commit

mkdir -p observability/costs
git add observability/costs/YYYY-MM-DD-costs.md MODEL_ROUTING.md
git commit -m "Cost snapshot: YYYY-MM-DD ($X,XXX monthly average)"

Cadence

Quarterly, aligned with the assessment cadence. The recommended workflow:

1. Run /assess (quarterly)
2. Run /cost-capture (same session or same week)
3. Run /harness-health (reads both)
4. Review the portfolio dashboard (shows cost trends if available)

What This Skill Does NOT Do

• Access billing APIs directly (the user reads their dashboard)
• Make routing changes without user approval
• Require exact per-project attribution (estimates are fine)
• Replace financial tooling (this is engineering visibility, not

accounting)