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 fzfclee/consulting-skills --skill inductive-reasoninggit clone --depth 1 https://github.com/fzfclee/consulting-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/fzfclee/consulting-skills/inductive-reasoning)<a href="https://agentmods.dev/skills/fzfclee/consulting-skills/inductive-reasoning"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/inductive-reasoning/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/fzfclee/consulting-skills/inductive-reasoning"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/inductive-reasoning.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 | $0.00059 | $0.00708 |
| Opus 5 | $0.00030 | $0.00354 |
| Sonnet 5 | $0.00012 | $0.00142 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
inductive-reasoning 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 9d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inductive Reasoning
Use this skill to infer a likely pattern or general rule from observed evidence.
Method Notes
- Inductive reasoning moves from specific observations to a broader pattern or generalization.
- Inductive conclusions are probabilistic, not certain.
- The method should make sample size, representativeness, exceptions, and confidence visible.
- It is useful for customer research, repeated stakeholder behavior, market signals, operational symptoms, and trend interpretation.
Required Inputs
Collect or infer these inputs before execution:
- observations, examples, cases, data points, quotes, or events
- source and timing of observations
- population or context being generalized to
- known exceptions
- decision or hypothesis the pattern will inform
If an input is missing, mark it as missing, state the assumption used, and add a validation action.
When Not To Use
Do not use when the conclusion must follow from formal rules or fixed criteria. Use deductive-reasoning instead.
Step-by-Step Execution
| Step | Required input | How to execute | Output |
|---|---|---|---|
| Define the inference question | Decision context, target population. | State what pattern or generalization is being tested. | Inference question. |
| List observations | Cases, data points, quotes, events. | Put each observation in a separate row with source and timing. | Observation table. |
| Cluster patterns | Observation table. | Identify repeated behaviors, causes, needs, outcomes, or signals. | Pattern candidates. |
| Test strength | Sample size, representativeness, consistency. | Rate each pattern by frequency, diversity of support, and evidence quality. | Pattern strength table. |
| Look for exceptions | Known counterexamples, missing segments. | Identify observations that contradict or limit the pattern. | Exception list. |
| State likely generalization | Pattern strength and exceptions. | Write the conclusion with confidence and boundary conditions. | Inductive conclusion. |
| Define validation | Weakest evidence gaps. | Specify what additional evidence would strengthen or weaken the pattern. | Validation plan. |
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.
- 9d ago First seen · 78 lines · 59 tokens per session scan A 9b0879f8123c
inductive-reasoning is a skill published in the GitHub repository fzfclee/consulting-skills (4 stars, last pushed 21d ago), licensed Apache-2.0. It adds 59 tokens to every session and 708 once invoked, about $0.0003 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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