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/synaptiai/agent-capability-standard/predictnpx skills add synaptiai/agent-capability-standard --skill predictgit clone --depth 1 https://github.com/synaptiai/agent-capability-standardWhat 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 | $0.00031 | $0.01786 |
| Opus 5 | $0.00015 | $0.00893 |
| Sonnet 5 | $0.00006 | $0.00357 |
| Haiku 4.5 | $0.00003 | $0.00179 |
Grade A, and why
predict 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 3d 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 — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent
Forecast future states or outcomes for a target based on current state, historical patterns, and assumed conditions. This capability consolidates all forecasting tasks (risk, impact, time, etc.) into a single parameterized operation.
Success criteria:
- Prediction for requested target and horizon provided
- Probability or confidence assigned to prediction
- Alternative outcomes considered
- Assumptions explicitly stated
Compatible schemas:
schemas/output_schema.yaml
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
target |
Yes | string | What to predict (metric, state, outcome, event) |
horizon |
No | string | Prediction timeframe (e.g., "1 week", "next release", "end of sprint") |
conditions |
No | object | Assumed conditions for prediction |
method |
No | string | Prediction approach (trend, model, heuristic) |
Procedure
-
Define prediction target: Clarify what outcome is being predicted
- Specify the metric, state, or event to forecast
- Establish the prediction horizon
- Note any boundary conditions
-
Gather historical data: Collect relevant past observations
- Identify patterns and trends
- Note data quality and coverage
- Look for relevant precedents
-
Establish conditions: Document assumptions about the future
- Note what must remain constant
- Identify key variables that could change
- Consider external factors
-
Generate prediction: Forecast the most likely outcome
- Apply trend analysis or modeling
- Calculate probability of primary prediction
- Identify alternative outcomes
-
Consider alternatives: Evaluate other possible outcomes
- List plausible alternative scenarios
- Assign rough probabilities to alternatives
- Note what would cause each alternative
-
Ground prediction: Document evidence and reasoning
- Reference data supporting the prediction
- Note the reasoning chain
- Explicitly state all assumptions
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 237 lines · 31 tokens per session scan A a44e44f891f7
predict is a skill published in the GitHub repository synaptiai/agent-capability-standard (4 stars, last pushed 3d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,786 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 2026-08-31.
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