Experiential is an open-source model gateway and router, meaning a service that gives agents one API for hosted, user-provided, local, and custom language models. It is for teams that need to choose models, control access and spending, and route production requests according to quality, speed, or cost. The catalogue entries provide agent skills and instructions for operating or configuring the gateway.
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 experientiallabs/experiential --skill ready-for-mergegit clone --depth 1 https://github.com/experientiallabs/experientialWrote 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/experientiallabs/experiential/ready-for-merge)<a href="https://agentmods.dev/skills/experientiallabs/experiential/ready-for-merge"><img src="https://agentmods.dev/badge/skills/experientiallabs/experiential/ready-for-merge/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/experientiallabs/experiential/ready-for-merge"><img src="https://agentmods.dev/badge/skills/experientiallabs/experiential/ready-for-merge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00078 | $0.01632 |
| Opus 5 | $0.00039 | $0.00816 |
| Sonnet 5 | $0.00016 | $0.00326 |
| Haiku 4.5 | $0.00008 | $0.00163 |
Grade A, and why
ready-for-merge 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ready for Merge
This is the mandatory gate before merging any PR in this repository. Do not tell the user a PR is ready to merge until every step below has been completed and passes.
Address Greptile as soon as a PR exists. When you open or update a PR, run Step 2 in the same turn: fetch Greptile comments, fix valid findings, reply, and resolve threads. Do not leave Greptile feedback for a later merge pass.
This skill never merges the PR. Merging is the user's decision alone — do not run
gh pr merge (or click-through equivalents) even if everything passes, and even if merging was
approved earlier in the conversation. The skill ends by handing the PR back to the user.
Work against the PR for the current branch (gh pr view --json number,url,headRefName). If no
PR exists, stop and tell the user.
Step 1 — Code review with fixes, scaled to the PR
Look at the PR's diff (gh pr diff <number> --stat and the diff itself) and pick the
code-review effort level that matches its breadth and risk — don't default to the maximum:
- low — mechanical or single-concern changes: a flag flip, a docstring/docs edit, a dependency bump, a few-line fix with an obvious test.
- medium — a small focused change: one behavior touched across a handful of files, new code paths that are well covered by tests. Most small PRs land here.
- high — a multi-file feature, changes to shared infrastructure, or anything where a subtle interaction with existing callers is plausible.
- xhigh — large or risky PRs: core engine/provider seams, data-loss or security surface, broad refactors, anything hard to roll back once merged.
State the level you chose and why in one sentence, then run the code-review skill with args
<level> --fix.
Let it finish and apply its fixes before moving on. If it applied changes, re-run the project gate afterwards (see Step 3).
Step 2 — Resolve every review comment on the PR
Fetch all comments and review threads on the PR — from Cursor (bugbot), Greptile, any other bot reviewers, and human reviewers:
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 · 128 lines · 78 tokens per session scan A 2b73f0bf18fc
ready-for-merge is a skill published in the GitHub repository experientiallabs/experiential (3,669 stars, last pushed today), licensed Apache-2.0. It adds 78 tokens to every session and 1,632 once invoked, about $0.0004 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 2026-08-30.
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