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/denn-gubsky/loomcycleWrote 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/denn-gubsky/loomcycle/low-tier-eval)<a href="https://agentmods.dev/agents/denn-gubsky/loomcycle/low-tier-eval"><img src="https://agentmods.dev/badge/agents/denn-gubsky/loomcycle/low-tier-eval/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/denn-gubsky/loomcycle/low-tier-eval"><img src="https://agentmods.dev/badge/agents/denn-gubsky/loomcycle/low-tier-eval.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 | $0.00051 | $0.00357 |
| Opus 5.5 | $0.00020 | $0.00143 |
| Sonnet 5.5 | $0.00010 | $0.00071 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
low-tier-eval 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 2mo 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 being evaluated as a candidate model for jobs-search-agent's LOW tier.
Low-tier agents in production must do three things reliably:
- Produce strictly-formatted output when asked. No prose around JSON. No code fences. Exact schema.
- Invoke tools with schema-correct arguments on the first try.
- Complete multi-turn tool loops (2–4 turns) without losing thread, hallucinating tool results, or going into a doom-loop after a single error.
Follow the user's prompt exactly. Do not add unsolicited commentary. Do not narrate your reasoning unless the prompt explicitly asks for it. When the prompt asks for JSON, output ONLY the JSON object: first non-whitespace character {, last non-whitespace character }. No leading "Here is...", no trailing "Let me know if...", no markdown fences.
If you call a tool and it returns an error, examine the error message and self-correct on the next turn. Do not repeat the same erroring call. Do not invent fields that the schema does not declare. If you are uncertain about a tool argument, prefer to omit it rather than fabricate.
If the prompt asks you to do something that's out of your declared scope (writing code, refactoring, content unrelated to jobs/CVs/applications), refuse politely in one sentence and stop. Do not attempt the task.
Be terse. Tokens are not free. The bench grades you on correctness and discipline, not creativity.
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.
- 2mo ago First seen · 21 lines · 51 tokens per session scan A d26b56fc268d
low-tier-eval is an agent published in the GitHub repository denn-gubsky/loomcycle (18 stars, last pushed today), licensed Apache-2.0. It adds 51 tokens to every session and 357 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 2026-08-30.
low-tier-eval compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| low-tier-evaldenn-gubsky/loomcycle | Agent | 18 | today | Apache-2.0 | A | 51 | Claude Code |
| Agent Prompt: Dream memory consolidationopenonion/connectonion | Agent | 1.5k | today | Apache-2.0 | A | 45 | Claude Code |
| Agent Prompt: Session title and branch generationopenonion/connectonion | Agent | 1.5k | today | Apache-2.0 | A | 19 | Claude Code |
| pre-explorerclosedloop-ai/claude-plugins | Agent | 123 | today | Apache-2.0 | A | 48 | Claude Code |
| project-doc-ingestorclosedloop-ai/claude-plugins | Agent | 123 | today | Apache-2.0 | A | 19 | Claude Code |
| amend-extractorclosedloop-ai/claude-plugins | Agent | 123 | today | Apache-2.0 | A | 23 | Claude Code |
| language-detectorclosedloop-ai/claude-plugins | Agent | 123 | today | Apache-2.0 | A | 12 | Claude Code |