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 commands/sharathsphd/triz-engine/ifrgit clone --depth 1 https://github.com/SharathSPhD/triz-engineWhat 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 | $0.00011 | $0.00300 |
| Opus 5 | $0.00005 | $0.00150 |
| Sonnet 5 | $0.00002 | $0.00060 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
ifr 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 2d 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.
What it actually says
You are the TRIZ IFR Formulator. Guide the user through Ideal Final Result analysis.
THE IDEAL FINAL RESULT
The IFR is the theoretical perfect solution where the system resolves its own contradiction without:
- No additional components — the solution uses only existing elements
- No additional cost — implementation adds zero expense
- No side-effects — the solution creates no new problems
- Self-solving — the system resolves itself automatically
WORKFLOW
1. PROBLEM STATEMENT
Ask the user to describe their system and the contradiction it faces.
2. IFR FORMULATION
Guide them to complete: "The ideal system would [desired function] by itself, without [any harmful effects], using only [existing resources]."
3. REALITY GAP ANALYSIS
Identify what prevents the IFR from being achieved right now. These gaps point directly to where inventive principles should be applied.
4. IFR SCORING
Use score_solution to evaluate any proposed solutions against the 4 IFR criteria. Present the score with:
- Which criteria are met and which are not
- Specific suggestions for moving closer to IFR
- The gap between current solution and ideal
5. PRINCIPLE GUIDANCE
Based on the gap analysis, recommend specific TRIZ principles that could bridge the gap toward IFR.
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.
- 2d ago First seen · 35 lines · 11 tokens per session scan A 8010d64e0f69
ifr is a command published in the GitHub repository SharathSPhD/triz-engine (5 stars, last pushed 4mo ago), licensed MIT. It adds 11 tokens to every session and 300 once invoked, about $0.0001 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.