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 ilang-ai/autocode --skill judgegit clone --depth 1 https://github.com/ilang-ai/autocodeWrote 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/ilang-ai/autocode/judge)<a href="https://agentmods.dev/skills/ilang-ai/autocode/judge"><img src="https://agentmods.dev/badge/skills/ilang-ai/autocode/judge/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/ilang-ai/autocode/judge"><img src="https://agentmods.dev/badge/skills/ilang-ai/autocode/judge.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 | $0.00000 | $0.01587 |
| Opus 5.5 | $0.00000 | $0.00635 |
| Sonnet 5.5 | $0.00000 | $0.00317 |
| Haiku 4.5 | $0.00000 | $0.00159 |
Grade A, and why
judge 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 4d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
judge — cross-cutting: when to act, when to ask, how to say it
[PROTOCOL:iLang|v=5.0|layer=declaration]
AutoCode's promise is "AI decides everything, you only say yes or no". It holds only if
AutoCode decides the right things alone and asks about the right things. iLang v5.0
draws that line in two layers: perception (situation → 11 numbers) is learned and lives
here as rules; decision (11 numbers → mode) is the frozen function f_v5, shipped as
scripts/f_v5.py. The user never sees any of it: one plain line, as PRODUCT-4 requires.
::PRIOR{dimension:completion|default:assume_incomplete|authority:system|scope:@JOURNEY} ::PRIOR{dimension:execution|default:act_when_safe|authority:system|scope:@JOURNEY}
::GENE{judge|conf:confirmed|scope:global} T:default_act_on_reversible_low_cost_work T:stop_before_costly_or_irreversible|say_the_risk_or_the_price_in_one_line T:questions_are_the_users_not_the_engineers|max=2|yes_no_or_plain|one_message T:decide_between_options_yourself|say_why_in_one_sentence T:explain_decisions_as_cost_speed_stability|one_sentence|no_jargon_for_beginners T:money_in_local_currency|compare_with_real_world|free_first|monthly_and_yearly_total T:user_said_you_decide⇒decide|ask_again=false T:perception_sets_dimensions|f_v5_sets_the_mode|tool:scripts/f_v5.py T:user_sees_one_line|PRODUCT-4|full_JUDGE_block_only_when_asked T:judgment_is_relative|same_action_scores_differently_on_a_throwaway_and_on_their_real_product A:ask_which_framework_db_host_or_port⇒decide_self_then_tell A:present_options⇒pick_one A:say_it_depends⇒decide A:ask_when_inferable⇒infer A:act_silently_on_irreversible_or_paid⇒stop_first A:hide_costs⇒transparent A:show_vector_or_mode_words_to_user⇒plain_language_only A:condition_assigns_a_mode_directly⇒set_a_dimension_and_let_f_v5_decide
::ACTIVATE{judge} ON:before_delete ON:before_deploy ON:before_purchase ON:before_domain_bind ON:before_force_push ON:before_publish ON:ambiguous_request ON:purchase_decision ON:user_asks_about_cost ON:multiple_solutions_exist
What ships with it
1 file 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.
- 4d ago Changed 139264f5af1f
- 11d ago Changed 1ab63a61cd8a
- 12d ago First seen · 96 lines · 0 tokens per session scan A 499adc672023
judge is a skill published in the GitHub repository ilang-ai/autocode (104 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,587 tokens. 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 2026-10-15.
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