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/ayushparkara/syntra/execute-plannpx skills add AyushParkara/syntra --skill execute-plangit clone --depth 1 https://github.com/AyushParkara/syntraWrote 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/ayushparkara/syntra/execute-plan)<a href="https://agentmods.dev/skills/ayushparkara/syntra/execute-plan"><img src="https://agentmods.dev/badge/skills/ayushparkara/syntra/execute-plan.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00365 |
| Opus 5 | $0.00017 | $0.00182 |
| Sonnet 5 | $0.00007 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
execute-plan 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 6d 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 executing an already-approved plan. The plan is the contract — follow it; do not silently redesign mid-execution.
Method (one step at a time, never batch blindly):
- Take the NEXT pending step only. Re-read what it produces and how it's verified.
- Do exactly that step. Build on prior steps' results; do not re-decide settled choices.
- Checkpoint before moving on: verify the step's stated success criterion (run the test, check the file, confirm the output). State the evidence plainly.
- If it passed → mark done, go to the next step.
- If it failed → record WHY (the exact error), and either fix-in-place or add a targeted repair step. Do NOT proceed past a broken step hoping it sorts itself out.
Rules:
- A step is "done" only with concrete evidence, never on intent or a plausible-looking diff.
- If reality contradicts the plan (a step is wrong/impossible), STOP and flag it for re-planning — don't improvise a different plan in your head.
- Stay in scope: deliver the step, not unrequested extras (scope creep is a defect).
- Respect the loop's bounds — if you've hit the same wall twice, stop and escalate, don't keep retrying the identical approach.
Output per step:
STEP <id>: <what you did>
EVIDENCE: <test passed / file written / command output>
STATUS: done | failed(<reason>)
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.
- 6d ago First seen · 33 lines · 35 tokens per session scan A b41c529df922
execute-plan is a skill published in the GitHub repository AyushParkara/syntra (5 stars, last pushed 25d ago), licensed Apache-2.0. It adds 35 tokens to every session and 365 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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