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BF skill-sediment

Install and operate the OpenClaw skill-sediment plugin extension (turns successful conversations into auto-generated SKILL.md files, then promotes them to skills/). Covers: install (with interactive agent selection), heal (self-repair: detect and fix whitelist/file loss, supplement missing validAgentId, auto-restart gateway), doctor (diagnostics), recover (restore after pod restart), status (sediment pool stats), config (current state), uninstall. Triggers on: sediment / auto-skill-sediment / install/port/clone sediment / sediment not working / sediment pool / uninstall sediment. Note: unrelated to the same-named Rust semantic-memory MCP (store/recall); does not cover OpenClaw installation itself nor publishing to Skill Hubs.

ClawHub Agent Skills author: Evan Song v1.0.2 MIT-0 15 files body ≈ 2 214 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Install and operate the OpenClaw skill-sediment plugin extension (turns successful conversations into auto-generated SKILL.md files, then promotes them to…

As a process F 45/100 · Will not run — References files that are not bundled: LICENSE

IntegrationKubernetesGitHubAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
93
Quality 40%
73
Run on models
none yet
Process rating
F
45/100
Will not run
References files that are not bundled: LICENSE
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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Secrets in code secret-high-entropy-token assets/plugin-source/src/auto-review.ts:63
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const UBA_EVENT_KEY = "skil…ION";
    quoted
  • low Dangerous commands cmd-privilege assets/plugin-source/src/skills-guard.ts:798
    Privilege escalation / world-writable permissions (string literal in code, not executed; documentation of a security skill)
    description: "setuid/setgid (privilege escalation mechanism)",
    code literalsecurity skill

A further 5 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 15. 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: LICENSE

Process rating: all ten parameters 45/100

Will not run. References files that are not bundled: LICENSE
  • 0Tools and files. 1 referenced file(s) missing: LICENSE
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 9 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 17 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2214 tokens
  • low 11 top-level sections: this looks like several domains in one skill

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 735: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This skill appears to install a powerful conversation-learning plugin that can persist, promote, modify, report, and delete skill content, with several controls and disclosures that are too broad or unclear for default installation.
LLM: suspicious (medium) · 13 Jul 2026