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.
git clone --depth 1 https://github.com/Digital-Threads/token-pilotWrote 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/agents/digital-threads/token-pilot/tp-review-impact)<a href="https://agentmods.dev/agents/digital-threads/token-pilot/tp-review-impact"><img src="https://agentmods.dev/badge/agents/digital-threads/token-pilot/tp-review-impact/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/agents/digital-threads/token-pilot/tp-review-impact"><img src="https://agentmods.dev/badge/agents/digital-threads/token-pilot/tp-review-impact.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 | $0.00059 | $0.01048 |
| Opus 5.5 | $0.00024 | $0.00419 |
| Sonnet 5.5 | $0.00012 | $0.00210 |
| Haiku 4.5 | $0.00006 | $0.00105 |
Grade A, and why
tp-review-impact 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 8d ago Changed 124308dfa3ea
- 23d ago Changed e3481d56f436
- 24d ago Changed 842e598ade75
- 29d ago Changed b624b4114f39
- 1mo ago Changed 4ccbb2dcbf8a
- 1mo ago Changed ea2a97cf4e75
- 1mo ago Changed · +5 lines fcd1049cf48c
- 1mo ago First seen · 57 lines · 59 tokens per session scan A d746c5d24ea7
tp-review-impact is an agent published in the GitHub repository Digital-Threads/token-pilot (5 stars, last pushed 8d ago), with no licence file. It adds 59 tokens to every session and 1,048 once invoked, about $0.0002 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.
Other agents, from other repositories
review-readability
R2 Readability reviewer — naming, complexity, intention, maintainability, review size, and context clarity.
review-reliability
R3 Reliability reviewer — behavior-first tests, coverage value, edge cases, determinism, contracts, and regressions.
review-risk
R1 Risk reviewer — security, privilege boundaries, data exposure, dependency risks, and merge-blocking vulnerabilities.
jd-fix-agent
You are a judgment-day surgical fix agent. Execute the fix instructions provided in the delegate prompt exactly.
review-refuter
Detached read-only refuter for one transaction-wide batch of inferential severe findings.
ijfw-code-fixer
Apply atomic per-finding code fixes triggered by code-review output. 3-tier verify (re-read → syntax-check → fallback). Defers logic-bug fixes to humans.