Agent skill

Vc Autoresearch

by withkynam in withkynam/vibecode-pro-max-kit

Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit.

MITAuto-check passedAgent Workflows

Install Vc Autoresearch

skills CLI
$ npx skills add withkynam/vibecode-pro-max-kit --skill vc-autoresearch -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install withkynam/vibecode-pro-max-kit vc-autoresearch --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/withkynam/vibecode-pro-max-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/vc-autoresearch .claude/skills/vc-autoresearch && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
vc-autoresearch
GitHub stars
1.1k
Token cost
~3.7k tokens
SKILL.md length
1,693 words
Files
10 (incl. scripts, references)
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit.

  • Works in 8 steps: Setup → Research → Convergence check → …
  • Tasks that involve Autonomous loops
  • SKILL.md covers When To Invoke, Who Runs This (Loop Driver), Subcommands and Parameters, plus 8 more sections
  • Runs JavaScript scripts from its folder; calls pnpm

What it does

Vc Autoresearch is an agent skill from withkynam/vibecode-pro-max-kit. Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit. Shared loop primitive for PVL, EVL, and standalone quality runs.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts and reference files (for example `domains/harness.md`, `references/autonomous-loop-protocol.md` and `references/git-memory-pattern.md`).

It sits in Agent Workflows, covering Autonomous loops. The repository describes itself as: Your AI forgets. This remembers. Spec-driven coding harness for vibecoders, product owners, CEOs and real builders — self-improving context memory, 15 agents, 33 skills working…. The licence is MIT.

When your agent uses it

  • Tasks that involve Autonomous loops

Example prompts

  • “/vc-autoresearch”

Requirements

  • Node.js

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Setup
  2. Research
  3. Convergence check
  4. Termination check (non-success)
  5. Write iteration report
  6. Fix
  7. Safety check
  8. Loop

What it can do on your machine

Read from SKILL.md and the folder at commit 3bcb2f9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • pnpm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pnpm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Vc Autoresearch loads about 3.7k tokens when it runs, and up to ~9k if it reads all its reference files. Until then it costs about 41 tokens; SKILL.md has 1,693 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from withkynam/vibecode-pro-max-kit at commit 3bcb2f9, republished under its MIT licence (© withkynam). 1,693 words, ~3,735 tokens.

Download SKILL.mdSave it as .claude/skills/vc-autoresearch/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
vc-autoresearch
description
Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit. Shared loop primitive for PVL, EVL, and standalone quality runs.
argument-hint
[domain] [corpus path(s)] [verify: command] [max_iterations: N]
trigger_keywords
autoresearch, harden spec, fix all errors, improve coverage, iterative improvement, gap loop
layer
contract
metadata.author
vibecode-pro-max-kit
metadata.version
1.0.0

vc-autoresearch

Output style: Follow process/development-protocols/communication-standards.md — answer-first, plain language, no unexplained jargon, TL;DR on long responses.

Reusable loop primitive. Runs: find gaps → write report → fix → check → repeat.

Used directly for spec/doc/UX hardening. Wired into PVL (plan-validate-fix loop — the fix cycle between writing a plan and approving EXECUTE) and EVL (execute-validate-fix loop — the confirmation run after EXECUTE) as the shared bookkeeping layer.


When To Invoke

  • Standalone: user says "harden this spec", "fix all lint errors", "improve test coverage"
  • PVL: the ORCHESTRATOR invokes it when vc-validate-agent returns a first-pass CONDITIONAL/BLOCKED verdict (validate-fix loops are needed)
  • EVL: the ORCHESTRATOR invokes it at the EVL confirmation run — unconditionally after every EXECUTE DONE, before UPDATE PROCESS

Do NOT invoke during RESEARCH or INNOVATE phases.

Who Runs This (Loop Driver)

The ORCHESTRATOR is the loop driver. It executes every bookkeeping step itself:

  • Step 0 setup — creates the task folder and the results.tsv tracking file.
  • Cycle counter + per-cycle iteration report — writes one report file per loop iteration.
  • TSV row — appends a row to results.tsv after each cycle.
  • Plateau/cap/regression checks — stops the loop when no progress is made for 3 cycles (HALT_PLATEAU — no improvement after 3 tries), when the hard 10-cycle limit is hit (HALT_CAP), or when a test that was passing now fails (HALT_REGRESSION).

Subagents (vc-validate-agent, vc-tester, vc-plan-agent, vc-execute-agent) are fire-and-forget: they emit a verdict and terminate. They cannot invoke this skill on the orchestrator's behalf, cannot loop themselves, and cannot spawn each other.

If no one runs Step 0, the loop never exists and verdicts silently become "proceed" — that failure mode is exactly what this section forbids.

Per-verdict routing tables: process/development-protocols/orchestration.md §PVL/EVL Loop Routing.


Subcommands

SubcommandDoesStops when
vc-autoresearch (core)find gaps → fix → repeatagents find no gaps OR metric goal hit
vc-autoresearch:probe8 personas interrogate the corpus until saturationno new constraints for 3 rounds
vc-autoresearch:reasonadversarial debate with blind judges until convergencejudges converge or iteration cap
vc-autoresearch:evalsanalyze TSV results — trends, plateaus, recommendationsN/A (analysis only)

Not ported (already covered by existing vc-system skills): debug → vc-debugger, security → vc-security, scenario → vc-scenario, predict → vc-predict.


Parameters

ParameterRequiredDefaultNotes
domain:yes—spec / tests / ux / docs / plan / errors
corpus:yes—file glob(s) or path list to investigate
verify:no—shell command that outputs a number; required for "hit the metric goal" mode
target:no0the number verify: must reach (lower-is-better assumed; use target_direction: higher to flip)
guard:no—safety shell command that must pass after every fix batch
frozen_files:no—glob pattern(s); any file matching is excluded from the fix corpus and must never be modified by a fix agent
max_iterations:noper domainhard cap on loop cycles
severity_escalation_at:no7after this many iterations, stop fixing CONCERN findings (move to backlog)
consecutive_all_clear:no2how many consecutive zero-gap iterations before SUCCESS
research_agents:noper domainnumber of parallel research agents
fix_agents:noper domainnumber of parallel fix agents
feature:noinferredfeature folder name for report output paths
task_slug:noautotask folder slug; auto-generated as autoresearch-{domain}-{YYMMDD}
auto_run:noprompttrue = no pauses; false = confirm before each fix batch; under /goal always true

Canonical Domain Defaults

Full configs in process/development-protocols/vc-autoresearch-spec.md §Canonical domain configs.

DomainResearch agentsFix agentsMax iterationsEscalation atGuard
spec23157none
tests2220—pnpm test
ux22105pnpm typecheck
docs128—node validator script
plan113—none
errors1220—none
harness2210—pnpm test:runtime-harness:unit

* harness full config: .claude/skills/vc-autoresearch/domains/harness.md


Loop Execution

Step 0 — Setup
  1. Parse parameters, apply domain defaults for any missing values
  2. If auto_run: not set and NOT under /goal: prompt once — "Auto-run (no pauses) or confirm before each fix batch?" Choice is sticky for the full loop.
  3. Create task folder: process/features/{feature}/active/{task_slug}_{dd-mm-yy}/
  4. Initialize TSV at {task_folder}/results.tsv with header row and baseline row (iteration 0, gaps_found: TBD, loop_status: baseline)
Step 1 — Research

Spawn research_agents: parallel agents. Each agent:

  • Reads the corpus files assigned to it
  • Investigates its thread list (cross-file consistency, missing cases, contradictions, undefined behaviors, etc.)
  • Returns a structured gap list: SEVERITY: FAIL | CONCERN | OBSERVATION per finding

Collect all findings. Count: gaps_found, fail_count, concern_count.

Apply severity floor: if iteration > severity_escalation_at, discard CONCERN findings (add to backlog section of report — do not fix).

Step 2 — Convergence check

"Until agents find no gaps" (no verify: param):

  • If all agents returned zero findings above the severity floor: increment consecutive_all_clear counter
  • If counter >= consecutive_all_clear: → SUCCESS
  • Else: reset counter, continue to Step 3

"Hit the metric goal" (verify: param set):

  • Run verify command, parse numeric output
  • If output reaches target: → SUCCESS
  • Else: continue to Step 3
Step 3 — Termination check (non-success)

Check in priority order:

  1. PLATEAU — gaps_found unchanged or increased for 3 consecutive iterations → HALT_PLATEAU
  2. CAP — iteration >= max_iterations → HALT_CAP
  3. REGRESSION — more than 2 new gaps in areas that were gap-free last iteration → HALT_REGRESSION (always pauses for user, even under /goal)

If none triggered: continue to Step 4.

Step 4 — Write iteration report

Write a NEW per-iteration report file: {task_folder}/{task_slug}-iteration-{NNN}_REPORT_{dd-mm-yy}.md — {NNN} is the zero-padded 3-digit iteration number (001, 002, … 042), so files sort correctly and every iteration is uniquely named no matter how many run.

ONE FILE PER ITERATION — hard rule. NEVER append iterations to a single rolling file (no ITERATION-NOTES.md, no shared {task_slug}_REPORT_*.md updated in place). The rolling cross-iteration view is results.tsv, nothing else.

Append a row to {task_folder}/results.tsv.

If auto_run: false: surface gap summary, wait for user confirmation before fixing.

Step 5 — Fix

Spawn fix_agents: parallel agents. Each agent:

  • Receives its assigned gap IDs and file targets
  • Applies fixes
  • Reports: APPLIED (fixed in this iteration) or BACKLOG (deferred, with reason)
Step 6 — Safety check

If guard: is set: run guard command.

  • Passes → loop back to Step 1
  • Fails → revert fix batch, log regression flag, retry this iteration. If regression budget exceeded (> 2 flags in one iteration) → HALT_REGRESSION
Step 7 — Loop

Increment iteration counter. Go to Step 1.


Termination Output

On any terminal state, write final iteration report with loop_status: set, then emit:

AUTORESEARCH COMPLETE
Domain:          {domain}
Iterations run:  N
Terminal state:  SUCCESS | HALT_PLATEAU (no progress after 3 cycles) | HALT_CAP (10-cycle hard limit) | HALT_REGRESSION (passing test now fails) | HALT_SEVERITY (critical gap found)
Gaps remaining:  N (FAIL: N, CONCERN: N)
Files updated:   [list]
Report:          {task_folder}/{task_slug}-iteration-{NNN}_REPORT_{dd-mm-yy}.md  (final iteration)
TSV:             {task_folder}/results.tsv

Show full SKILL.md (699 more words)Show less

PVL Wiring

When vc-autoresearch is the bookkeeper for a PVL (plan-validate-fix loop):

  • domain: plan, corpus: = the plan .md file
  • Research step = vc-validate-agent runs V1–V3 gates; autoresearch does NOT run these itself. The validate step itself fans out in parallel via vc-validate-findings (Layer 1 dimension agents + Layer 2 feasibility agents) — that parallelism is owned by vc-validate-agent.
  • Gap signal = FAIL / CONDITIONAL / CONCERN from validate-agent
  • Fix step (parallel) = when the gap set spans independent plan sections, the orchestrator spawns multiple parallel plan-fix agents, one per independent gap group, partitioned so no two agents edit the same plan region. fix_agents: defaults to the count of independent gap groups (cap to the plan-domain default unless raised). Each fixer is scoped to its assigned gap IDs only. When gaps are interdependent or touch one section, fall back to a single plan-fix agent.
  • Convergence = validate-agent returns PASS → SUCCESS
  • Cap = 10 plan-validate-fix loops
  • Per-cycle report = every PVL cycle writes its own report file {task_folder}/{plan-slug}-pvl-iteration-{NNN}_REPORT_{dd-mm-yy}.md (zero-padded {NNN}) capturing: gaps found (with severity), fixes applied vs backlogged, and the validate verdict for that cycle. Never a single rolling notes file.

Boundary:

  • vc-autoresearch owns: iteration counter, plateau detection, per-cycle iteration report, regression flag, parallel-fix partitioning (which gap groups go to which fixer) — all executed by the ORCHESTRATOR at each cycle boundary; no agent runs these implicitly
  • vc-validate-agent owns: V1–V7 gate sequence + its own Layer-1/Layer-2 fan-out, SUPPLEMENT REQUEST format, validate-contract write, known-gap exclusion — it emits its verdict and terminates; the orchestrator re-spawns it from V1 after each SUPPLEMENT_APPLIED

EVL Wiring

When vc-autoresearch is the bookkeeper for an EVL (execute-validate-fix loop):

  • domain: tests, verify: = validate-contract gate commands (read from contract — never invented)
  • Research step = a SPAWNED vc-tester agent runs the validate-contract fully-automated gate commands (vc-tester may run independent gate groups in parallel). The orchestrator NEVER runs gate commands in its own shell — a gate result not produced by a vc-tester spawn does not count as an EVL confirmation, even if green.
  • Gap signal = failing gate (non-zero exit)
  • Fix step (parallel) = when multiple independent gates fail across non-overlapping file groups, the orchestrator spawns multiple parallel execute-fix agents (vc-execute-agent in supplement mode), one per failing gate / file group, partitioned so no two agents edit the same file. Each fixer is scoped to exactly its failing gate — no scope expansion. When failing gates share files or a single root cause, fall back to a single execute-fix agent. The fix is ALWAYS a vc-execute-agent spawn — the orchestrator never edits source files itself, no matter how small the fix.
  • Convergence = all validate-contract fully-automated gates pass → SUCCESS
  • Cap = 10 execute-validate-fix loops
  • Per-cycle report = every EVL cycle writes its own report file {task_folder}/{plan-slug}-evl-iteration-{NNN}_REPORT_{dd-mm-yy}.md (zero-padded {NNN}) capturing: which gates ran, which failed (with trimmed failure output), fixes applied, and the re-run result for that cycle. Never a single rolling notes file.

Boundary:

  • vc-autoresearch owns: iteration counter, plateau detection, TSV log, per-cycle iteration report, HANDOFF SUMMARY trigger, parallel-fix partitioning (which failing gate goes to which fixer) — all executed by the ORCHESTRATOR at each cycle boundary; no agent runs these implicitly
  • vc-tester owns: which gate commands to run, HANDOFF SUMMARY format, agent-probe re-invocation — its confirmation run is UNCONDITIONAL after every EXECUTE DONE (execute-agent's internal iterate-until-green loop never substitutes for it); it reports failing gates and terminates; the orchestrator runs the fix cycle and re-spawns it

Iteration Report Format

See process/development-protocols/vc-autoresearch-spec.md §Iteration report for full frontmatter schema and body sections.

Gap entry format:

### GAP-I{N}-{ID} — {short title}
- **SEVERITY:** FAIL | CONCERN | OBSERVATION
- **LOCATION:** {file} §{section}
- **GAP:** {what is missing or wrong}
- **RESOLUTION:** {what was changed}
- **STATUS:** APPLIED | BACKLOG

Each iteration report is written inside the active task folder as {slug}-iteration-{NNN}_REPORT_{dd-mm-yy}.md with {NNN} zero-padded to 3 digits (task-folder artefact colocation — never a sibling reports/ dir). One file per iteration; PVL/EVL cycles use the {plan-slug}-pvl-iteration-{NNN} / {plan-slug}-evl-iteration-{NNN} slug variants.


TSV Log Format

Header row:

iteration	timestamp	gaps_found	fail_count	concern_count	applied	saturation_status	loop_status	notes
  • Baseline row = iteration 0, before any fixes, loop_status: baseline
  • One row appended after each iteration's fix batch completes
  • saturation_status: ACTIVE | PLATEAU | SATURATED
  • loop_status: CONTINUE | HALTED_SUCCESS | HALTED_PLATEAU | HALTED_CAP | HALTED_REGRESSION

Run vc-autoresearch:evals {task_folder}/results.tsv to analyze trends and get a plateau/recommendation report.


Hook Notes

  • iteration-context.cjs — injects last 3 TSV rows at UserPromptSubmit; must scan process/features/*/active/*/results.tsv (not project-root autoresearch/ paths)
  • session-init.cjs — active plan summary at SessionStart; adapted to scan process/general-plans/active/ and process/features/*/active/
  • stop-notify.cjs — terminal notification at SessionEnd; no changes needed
  • Do NOT register scout-block.cjs or privacy-block.cjs from the autoresearch reference repo — vc-system settings.json has superior versions; registering them would cause conflicts

© withkynam, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references) in .claude/skills/vc-autoresearch of withkynam/vibecode-pro-max-kit.

  • SKILL.md
  • domains/harness.md
  • references/autonomous-loop-protocol.md
  • references/git-memory-pattern.md
  • references/guard-and-noise.md
  • references/metric-library.md
  • references/results-logging.md
  • scripts/fixtures/validate-autoresearch-log/fail.tsv
  • scripts/fixtures/validate-autoresearch-log/pass.tsv
  • scripts/validate-autoresearch-log.mjs

Open the folder on GitHubat commit 3bcb2f9

Compare with similar skills

Vc Autoresearch next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Vc Autoresearch compared with similar skills
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Vc Autoresearch this skillwithkynam/vibecode-pro-max-kit1.1k—~3.7kAutomated safety check: PassMIT
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Ar Resumealirezarezvani/claude-skills28k—~529Automated safety check: PassMIT
ClawlaunchLeoYeAI/openclaw-master-skills2.2k—~5.9kAutomated safety check: PassMIT
Context ManagerMark393295827/third-brain-v7-skills141—~1.5kAutomated safety check: PassMIT
Show Me Your Work Decision Logcursor/plugins10k8 repos~1.6kAutomated safety check: PassNone

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Questions about Vc Autoresearch

What does Vc Autoresearch do?

Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit. Vc Autoresearch is an agent skill from withkynam/vibecode-pro-max-kit. Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit.

When should I use Vc Autoresearch?

Vc Autoresearch fits situations like: tasks that involve Autonomous loops.

How do I install Vc Autoresearch in Claude Code?

Run `npx skills add withkynam/vibecode-pro-max-kit --skill vc-autoresearch -a claude-code`. Or copy the skill folder (.claude/skills/vc-autoresearch in withkynam/vibecode-pro-max-kit) into .claude/skills/vc-autoresearch in your project. Claude Code loads it when a task matches its description.

How do I install Vc Autoresearch in Codex?

Run `npx skills add withkynam/vibecode-pro-max-kit --skill vc-autoresearch -a codex`. Or copy the skill folder (.claude/skills/vc-autoresearch in withkynam/vibecode-pro-max-kit) into .agents/skills/vc-autoresearch in your project. Codex loads it when a task matches its description.

Can I use Vc Autoresearch in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add withkynam/vibecode-pro-max-kit --skill vc-autoresearch -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vc-autoresearch, .gemini/skills/vc-autoresearch, .github/skills/vc-autoresearch and .opencode/skills/vc-autoresearch in your project.

What does Vc Autoresearch need to run?

Going by SKILL.md and its folder, Vc Autoresearch needs JavaScript for the scripts in its folder and the command-line tools its instructions call (pnpm). Our summary lists: Node.js.

Does Vc Autoresearch access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Vc Autoresearch safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Vc Autoresearch use?

Vc Autoresearch is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vc Autoresearch use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.3k tokens, read only when the agent opens those files.

What are the alternatives to Vc Autoresearch?

Skills that share tags, products or a category with Vc Autoresearch: Long Horizon Prompting (guanyang/open-agent-hub, 977 stars), Ar Resume (alirezarezvani/claude-skills, 28k stars), Clawlaunch (LeoYeAI/openclaw-master-skills, 2.2k stars) and Context Manager (Mark393295827/third-brain-v7-skills, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vc Autoresearch?

withkynam (a GitHub user) maintains it in withkynam/vibecode-pro-max-kit, which has 1,145 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 21, 2026.

Source: withkynam/vibecode-pro-max-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.