SKILLEMALL.ai

CF tb4-five-arm

在 Terminal-Bench 4.0 上做 codex harness 五臂对照(裸 codex / 原生 /goal / LoopX 三模式)。复用 SWE-Marathon 那套驱动,靠 WEN_BENCH 切换。重点是 TB4 相对 SWE-Marathon 的四处结构性差异——每一处踩错都**退出码 0、有轨迹、有分数**,只是分数不对。

huangruiteng/loopx Agent Skills author: huangruiteng Apache-2.0 1 file body ≈ 1 522 tokens Open the sourcegithub.com↗ analyzed 6 d ago

在 Terminal-Bench 4.0 上做 codex harness 五臂对照(裸 codex / 原生 /goal / LoopX 三模式)。复用 SWE-Marathon 那套驱动,靠 WENBENCH 切换。重点是 TB4 相对 SWE-Marathon 的四处结构性差异——每一处踩错都退出码…

As a process F 33/100 · No process to follow — References files that are not bundled: scripts/bench/tb4.sh, scripts/_is_done.py

ProcedureDockerSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
33/100
No process to follow
References files that are not bundled: scripts/bench/tb4.sh, scripts/_is_done.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/bench/tb4.sh
  • warning missing-ref reference to a missing file: scripts/_is_done.py
  • note edit-residue the text marks something as outdated (lines 167): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/bench/tb4.sh, scripts/_is_done.py
  • 0Tools and files. 2 referenced file(s) missing: scripts/bench/tb4.sh, scripts/_is_done.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1522 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 176: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.