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 drivestream-lab/prayog-skills --skill loop-specgit clone --depth 1 https://github.com/drivestream-lab/prayog-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/drivestream-lab/prayog-skills/loop-spec)<a href="https://agentmods.dev/skills/drivestream-lab/prayog-skills/loop-spec"><img src="https://agentmods.dev/badge/skills/drivestream-lab/prayog-skills/loop-spec/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/drivestream-lab/prayog-skills/loop-spec"><img src="https://agentmods.dev/badge/skills/drivestream-lab/prayog-skills/loop-spec.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 | $0.00081 | $0.03036 |
| Opus 5.5 | $0.00032 | $0.01214 |
| Sonnet 5.5 | $0.00016 | $0.00607 |
| Haiku 4.5 | $0.00008 | $0.00304 |
Grade A, and why
loop-spec 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 1mo 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop spec
Execute the per-wave Pass-1 loop:
implement TASK → check/test → fix → record local proof → repeat
→ write Wave-Execution + Forge commit_workspace readiness
→ stop at wave-acceptance (human prove + patch tip)
Closeout (/learning-extract → /ground-spec) is a separate Pass-2 after
human wave-acceptance — not this skill's job.
Content skills write locally and emit Forge readiness; they do not commit, push, branch, open PRs, label, create issues, or merge.
Conventions: prayog-skills/references/id-conventions.md,
prayog-skills/references/artifact-write-contract.md.
Canonical artifact after the wave is green:
{reports_dir}/Wave-Execution-{INIT}-W{N}.md.
NON-NEGOTIABLE
- Implement against the product spec only — do not implement scope from the next wave.
- Prerequisites — run only after
/pre-implementproduced a checklist with gate verdict PASS on the current wave. Do not run on an open Draft spec PR branch (chore/*-spec-*). The implementation plan must exist ondevelop(spec package merged withspec-lgtmon merge head). Wave head is bound by Forge/human context. Canonical §9 WorkManifest (prayog/v1) must already have passed contract validation at pre-implement. - Consume WorkManifest tasks — execute
TASK-*for this wave in dependency order (depends_onDAG within the wave). Remain within each TASK's declaredfiles[]path/action scope. Do not mutate the approved WorkManifest intent (no rewriting exit criteria, deps, or live contract in §9). Persist actual command/evidence results only inWave-Execution-{INIT}-W{N}.mdand the stage handoff. - After each TASK, run
{check_command}and{test_command}from the harness profile (ortests_readme) — check/unit layers only. Both must pass before recording the TASK complete. Implement co-shipped live FILE TASKs (scripts underlive_verify_dirand fixture packs underfixtures_dir) when the plan/manifest includes them — deliver stimulus + probes perlive-fixture-contract.md; do not execute live verify,verify_all, or{verify_command}as this skill's success bar, and never claim human smoke/sandbox success or opaque look-at pass. - Fix failures before moving to the next TASK — do not accumulate failures.
- When all TASKs are green: write
Wave-Execution-{INIT}-W{N}.md, emit completedTASK-*IDs/evidence (observed commands + results), fillcommit_workspacereadiness and completehandoff.forgefor nextwave-pr-action(open_draft_prrequires). Do not run/ground-specor/learning-extractin this hop. Do not self-approve the wave. Handoff MUST list human prove:{verify_command}, coveredCAP-*/J-*, fixture paths, and anyhuman_observationslook-ats. - Do not skip check/test steps to save time.
- Bind execution — each iteration names
TASK-W{n}-{nn}, the wave board issue URL/number, andimplements: [REQ-…]from the WorkManifest (board body is projection only). - Structured failures — on check/test failure, record under handoff
blockerstheTASK-*id plus command and short why; prepare optional issue-comment Forge readiness when tooling is authorized elsewhere. Do not advance while any TASK blocker remains. - Never commit or push inside this skill — not per TASK and not at wave
end. ForgeClient or
/commit-workspacepublishes the workspace tree to the bound wave head after this hop when the pin requires it.
What ships with it
4 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.
- 1mo ago Changed · +4 lines 5b85ad1d8bcd
- 2mo ago First seen · 217 lines · 81 tokens per session scan A e59692b05114
loop-spec is a skill published in the GitHub repository drivestream-lab/prayog-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 3,036 once invoked, about $0.0003 per session on Opus 5.5. 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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