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AF gr-backlinks

Systematic backlink building for indie founders. Covers 5 channel types ranked by GEO + SEO ROI: Wikipedia (entities), authoritative media (PR), industry reviews (G2/Capterra/Product Hunt), Reddit/Quora discussions, and HARO/Featured.com expert quotes. Designed for 0→1 sites where domain authority is the bottleneck. Aligns with 2026 Google/Bing GEO guidance: backlinks are the strongest brand-authority signal AI search engines use to decide citations. Defaults to dev/B2B link sources; for 2C products (education, consumer apps) authority links differ — see gingiris-seo-geo/references/2c-adaptation.md.

ClawHub Agent Skills author: Iris Wei v1.0.3 MIT-0 24 files body ≈ 3 197 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 35/100 · Will not run — References files that are not bundled: scripts/haro-helper.py

GeneratorMarketingtype 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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: scripts/haro-helper.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. 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: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/haro-helper.py
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: scripts/haro-helper.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/haro-helper.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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 9 mutating operations with no state check
  • 100Steps. 102 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3197 tokens
  • 100Progress reporting. Reports progress
  • low 16 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
  • -244 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 606: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 102 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This backlink skill is mostly transparent, but it includes public-platform influence guidance and some loosely scoped network/API behavior that users should review before installing.
LLM: suspicious (high) · 4 Aug 2026