compare-tasks

compare-tasks is a skill for Claude Code, Codex from aaif-goose/goose. It costs 16 tokens per session (2,430 once invoked), scanned A, original, Apache-2.0.

Instructions for comparing two Harbor benchmark runs on the same task, where a run is a recorded set of benchmark trials.

In plain words
What is it for?
They locate matching trial folders, verify their task names, compare headline results, and inspect the recorded outputs to identify the cause of the difference.
Why use it?
They help explain why two runs produced different results instead of only reporting that their scores differ.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is ./evals/harbor/cmd.py task "$RUN_A" "$TASK".

Good fit They locate matching trial folders, verify their task names, compare headline results, and inspect the recorded outputs to identify the cause of the difference.

Compare 6 skills from other repositories ↓
About the project

Goose is an open-source AI agent that runs on a computer as a desktop app, command-line tool, or API and can perform tasks beyond code completion. Developers and other users employ it for coding, research, writing, automation, and data analysis with different language-model providers and extensions. The catalogue add-ons define parts of its agent workflow and behavior.

aaif-goose/goose · 55,322 stars · on GitHub · goose-docs.ai

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/aaif-goose/goose
agentmods
npx agentmods add skills/aaif-goose/goose/compare-tasks

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for compare-tasks

README.md
[![agentmods](https://agentmods.dev/badge/skills/aaif-goose/goose/compare-tasks/github.svg)](https://agentmods.dev/skills/aaif-goose/goose/compare-tasks)
Your own site
<a href="https://agentmods.dev/skills/aaif-goose/goose/compare-tasks"><img src="https://agentmods.dev/badge/skills/aaif-goose/goose/compare-tasks/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.

agentmods 80×15 button for compare-tasks

Your own site · 80×15
<a href="https://agentmods.dev/skills/aaif-goose/goose/compare-tasks"><img src="https://agentmods.dev/badge/skills/aaif-goose/goose/compare-tasks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,430 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Snyk pass 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.02430
Opus 5.5 $0.00006 $0.00972
Sonnet 5.5 $0.00003 $0.00486
Haiku 4.5 $0.00002 $0.00243

Measured 1mo ago against content hash 6972b34c696f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

compare-tasks 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

evals/harbor/.agents/skills/compare-tasks/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Compare two harbor runs on one task

Use when given two harbor run names and a task name, and the goal is to understand why the two runs differ on that task — not just that they differ.

Inputs

  • RUN_A: harbor run name (e.g. sonnet46-full)
  • RUN_B: harbor run name (e.g. pi-sonnet46-full)
  • TASK: bare task name (e.g. extract-elf, not terminal-bench/extract-elf)
  • RUNS_DIR: defaults to evals/harbor/runs/ relative to the repo root

Procedure

1. Find each run's trial directory for the task

Harbor 0.8 names trial dirs <task>__<random-suffix> (e.g. extract-elf__bU3GHs4), not <task>.1. The suffix is unique per trial, so don't guess it — discover it from disk:

TRIAL_A_DIR=$(ls -d "$RUNS_DIR/$RUN_A/${TASK}__"*/ 2>/dev/null | head -1)
TRIAL_B_DIR=$(ls -d "$RUNS_DIR/$RUN_B/${TASK}__"*/ 2>/dev/null | head -1)

If either is empty, that run didn't include this task — stop and say so. (ls "$RUNS_DIR/$RUN_A/" shows what's there.)

If you want to confirm the match, every result.json carries task_name and trial_name:

jq '{task_name, trial_name}' "$TRIAL_A_DIR/result.json"

2. Headline facts

The fastest path is to let cmd.py task do it for you — it already prints status, reward, duration, tokens, turns, cost, error class, and the tail of the verifier stdout:

./evals/harbor/cmd.py task "$RUN_A" "$TASK"
./evals/harbor/cmd.py task "$RUN_B" "$TASK"

Only drop to raw jq against result.json if you need a field cmd.py task doesn't print. The actual shape (harbor 0.8 TrialResult):

jq '{
  reward: (.verifier_result.rewards.reward
           // (.verifier_result.rewards | to_entries | .[0].value)
           // null),
  rewards_all: .verifier_result.rewards,
  duration_seconds: ((.finished_at | fromdateiso8601) - (.started_at | fromdateiso8601)),
  input_tokens: .agent_result.n_input_tokens,
  cache_tokens: .agent_result.n_cache_tokens,
  output_tokens: .agent_result.n_output_tokens,
  cost_usd: .agent_result.cost_usd,
  error_type: .exception_info.exception_type,
  error_message: (.exception_info.exception_message // "" | split("\n")[0])
}' "$TRIAL_A_DIR/result.json"

Read the full file on GitHub · 228 lines

Changes

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.

  1. 1mo ago First seen · 228 lines · 16 tokens per session scan A 6972b34c696f

Subscribe to this mod's changes

compare-tasks is a skill published in the GitHub repository aaif-goose/goose (55,322 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 2,430 once invoked, about $0.0001 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.

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