SKILLEMALL.ai

BA novel-forge

Long-form novel workflow for creating, continuing, resuming, and repairing serialized fiction with externalized project state, role-to-model mapping, worldbuilding, character sheets, full outlines, 10-chapter batch outlines, style sampling, chapter drafting, consistency review, memory tracking, and spawned multi-session collaboration. Use when the user asks to start a novel project, continue or resume a draft, recover from truncation, assign models to roles, generate canon or chapters, review for consistency, or maintain a long-running fiction project across many chapters. Supports single-agent or multi-agent execution, with multi-agent as the default; when multi-agent is selected, first surface the available model inventory and the novel-writing role list, then ask the user for an explicit role→model mapping before any canon work. Once the user has provided the mapping, persist it in project state and drive stage work with `sessions_spawn` using the mapped roles rather than treating the mapping as passive metadata. The main session may only create the project shell and route work; it must not author canon files.

ClawHub Agent Skills author: 咲鹏 v2.0.0 MIT-0 14 files body ≈ 3 055 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process A 88/100 · Runs to the end — weak spots: running it twice, progress reporting

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
A
88/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1130 chars, limit 1024

Process rating: all ten parameters 88/100

  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 159 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 19 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3055 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +3Description length 1130: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 159 items
  • +3Output format is stated explicitly
  • +4Reference files are cited in the instructions (7 of 8)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: clean
Novel Forge is a disclosed file-backed novel workflow; its local reads, project writes, and multi-agent routing fit that purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026