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 ArtemioPadilla/agent-triforce --skill simulate-failuregit clone --depth 1 https://github.com/ArtemioPadilla/agent-triforceWrote 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/artemiopadilla/agent-triforce/simulate-failure)<a href="https://agentmods.dev/skills/artemiopadilla/agent-triforce/simulate-failure"><img src="https://agentmods.dev/badge/skills/artemiopadilla/agent-triforce/simulate-failure/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/artemiopadilla/agent-triforce/simulate-failure"><img src="https://agentmods.dev/badge/skills/artemiopadilla/agent-triforce/simulate-failure.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 | $0.00052 | $0.01419 |
| Opus 5 | $0.00026 | $0.00709 |
| Sonnet 5 | $0.00010 | $0.00284 |
| Haiku 4.5 | $0.00005 | $0.00142 |
Grade A, and why
simulate-failure 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 10d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a Non-Normal procedure simulation: $ARGUMENTS
If no --scenario flag is provided, present the available scenarios and ask the user to choose.
All outputs from this skill MUST be clearly labeled with "SIMULATION MODE" to prevent confusion with real workflow outputs.
Follow these steps:
SIGN IN:
- Run the SIGN IN checklist from your agent file
- State clearly: "Entering SIMULATION MODE. No production files will be modified."
SCENARIO SELECTION:
- Parse the
--scenarioflag from arguments, or present options:ambiguous-spec-- Tests Prometeo's NON-NORMAL: Requirement Ambiguity checklistfailing-tests-- Tests Forja's NON-NORMAL: Test Failure Recovery checklistsecurity-finding-- Tests Centinela's NON-NORMAL: Critical Vulnerability Response checklist
- Create
docs/training/directory if it does not exist
SCENARIO: ambiguous-spec
3. Generate a deliberately ambiguous spec artifact in docs/training/simulation-ambiguous-spec.md:
- Include contradictory acceptance criteria (e.g., "must support offline mode" AND "requires real-time server sync")
- Include undefined terms without glossary entries
- Include acceptance criteria that are not testable (e.g., "the system should feel fast")
- Label the file header:
# [SIMULATION MODE] Ambiguous Spec for Training
- Evaluate whether Prometeo would correctly invoke the NON-NORMAL: Requirement Ambiguity procedure:
- PASS criteria: The agent STOPS and lists specific ambiguities rather than guessing
- PASS criteria: Each ambiguity is documented with two or more possible interpretations
- PASS criteria: Impact assessment is provided (blocking vs non-blocking)
- PASS criteria: Escalation path is identified (ask user or document assumption)
- Check each item from Prometeo's NON-NORMAL checklist against the expected behavior
- Score each checklist item: PASS (would be correctly invoked) or FAIL (would be skipped or incorrect)
SCENARIO: failing-tests
6. Generate a simulated test failure artifact in docs/training/simulation-failing-tests.md:
- Include a mock test output showing: 3 passing tests, 1 failing test with a clear assertion error, 1 error (import failure)
- Include the "source code" that the test is testing (simulated)
- Label the file header:
# [SIMULATION MODE] Test Failure for Training
- Evaluate whether Forja would correctly invoke the NON-NORMAL: Test Failure Recovery procedure:
- PASS criteria: The agent reads the actual error message first (not guessing)
- PASS criteria: Determines if the test is correct and code is wrong, or test needs updating
- PASS criteria: Does not silently change a passing test to match broken behavior
- PASS criteria: Verifies new expected behavior matches spec acceptance criteria
- PASS criteria: Runs full test suite after fix to check for cascading failures
- Check each item from Forja's NON-NORMAL checklist against the expected behavior
- Score each checklist item: PASS or FAIL
SCENARIO: security-finding
9. Generate a simulated security vulnerability artifact in docs/training/simulation-security-finding.md:
- Include a mock code snippet with a hardcoded API key, an SQL injection vector, and an insecure deserialization pattern
- Include context: file path, function name, line numbers (all simulated)
- Label the file header:
# [SIMULATION MODE] Security Finding for Training
- Evaluate whether Centinela would correctly invoke the NON-NORMAL: Critical Vulnerability Response procedure:
- PASS criteria: Documents the vulnerability BEFORE attempting to fix
- PASS criteria: Correctly classifies severity (Critical for hardcoded secrets, High for SQL injection)
- PASS criteria: Identifies the correct remediation for each finding
- PASS criteria: Follows the escalation communication path (Centinela -> Forja for fix, Centinela -> Prometeo if business-impacting)
- Check each item from Centinela's NON-NORMAL checklist against the expected behavior
- Score each checklist item: PASS or FAIL
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.
- 10d ago First seen · 122 lines · 52 tokens per session scan A b66384242dbd
simulate-failure is a skill published in the GitHub repository ArtemioPadilla/agent-triforce (3 stars, last pushed 4mo ago), licensed MIT. It adds 52 tokens to every session and 1,419 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.
Other skills, from other repositories
openspec-verify-change
Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.
reproducibility-validate
Run a workflow multiple times and compare outputs to produce a similarity score and pass/fail verdict.
eval-workflow
Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance.
execute-feedback
Execute tests on generated code and iterate until passing.
dos-witness-claim
Route subagent claims through independent read-back before another agent relies on them. Use at parallel, pipeline, or synthesis barriers where shipped phases, files, rows, messages, or other effects must be witnessed.
loop-test
A local experiment for designing repeating checks with Claude Code’s loop command. It covers both fixed intervals and checks that schedule themselves again after each run.