Agent skill

Ds Finalize

by OpenLAIR in OpenLAIR/dr-claw

A skill your agent uses when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving.

MITAuto-check passed

Install Ds Finalize

skills CLI
$ npx skills add OpenLAIR/dr-claw --skill ds-finalize -a claude-code

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

GitHub CLI
$ gh skill install OpenLAIR/dr-claw ds-finalize --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/OpenLAIR/dr-claw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ds-finalize .claude/skills/ds-finalize && 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
ds-finalize
GitHub stars
1.2k
Token cost
~3.2k tokens
SKILL.md length
1,664 words
Files
3 (incl. references)
Skills in repo
35
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving.

  • Works in 7 steps: Consolidate the accepted evidence and… → Build the final claim ledger → Produce a final limitations and failure… → …
  • The quest is ready to consolidate final claims
  • SKILL.md covers Interaction discipline, Stage purpose, Use when and Do not use when, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ds Finalize is an agent skill from OpenLAIR/dr-claw. Use when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/finalization-checklist.md` and `references/resume-packet-template.md`).

The repository describes itself as: A Super AI Lab with massive AI Doctors as Assistants. Best IDE for Research via AI Power. The licence is MIT.

When your agent uses it

  • The quest is ready to consolidate final claims
  • Recommendations
  • Graph exports before stopping

Example prompts

  • “/ds-finalize”

Workflow steps

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

  1. Consolidate the accepted evidence and package inventory
  2. Build the final claim ledger
  3. Produce a final limitations and failure section
  4. Produce the final recommendation
  5. Build a resume or handoff packet
  6. Refresh the durable quest view
  7. Record the final decision

What it can do on your machine

Read from SKILL.md and the folder at commit d51b64e. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Ds Finalize loads about 3.2k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 1,664 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from OpenLAIR/dr-claw at commit d51b64e, republished under its MIT licence (© OpenLAIR). 1,664 words, ~3,218 tokens.

Download SKILL.mdSave it as .claude/skills/ds-finalize/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
ds-finalize
description
Use when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving.
skill_role
stage
license
MIT
metadata.author
ResearAI/DeepScientist
metadata.version
1.0.0

Finalize

Use this skill to close or pause a quest responsibly.

Interaction discipline

  • Follow the shared interaction contract injected by the system prompt.
  • For ordinary active work, prefer a concise progress update once work has crossed roughly 6 tool calls with a human-meaningful delta, and do not drift beyond roughly 12 tool calls or about 8 minutes without a user-visible update.
  • Do not emit another finalize progress update when the user-visible state is unchanged.
  • If the runtime starts an auto-continue turn with no new user message, keep finalizing from the durable quest state and active requirements instead of replaying the previous user turn.
  • If a threaded user reply arrives, interpret it relative to the latest finalize progress update before assuming the task changed completely.
  • When finalize reaches a real closure state, pause-ready packet, or route-back decision, send one threaded artifact.interact(kind='milestone', ...) update that names the recommendation, why it is the right call, and any reopen condition that still matters.
  • True quest completion still requires explicit user approval through the runtime completion flow before calling artifact.complete_quest(...).
  • Rechecking that the same bundle files still exist, or re-aligning status surfaces without changing the closure judgment, does not by itself count as a fresh milestone.
  • Hard execution rule: if this stage needs terminal work such as Git inspection, packaging checks, document builds, or file inspection, every such command must go through bash_exec.

Stage purpose

The finalize stage should not pretend every line succeeded. It should produce the most accurate final state of the quest:

  • what is supported
  • what is only partially supported
  • what failed
  • what remains open
  • whether the right move is stop, archive, publish, or continue later

Finalize is not just a short summary. It is the durable closure protocol that turns a long-running research graph into a recoverable stopping point, a publishable handoff, or an honest continue-later checkpoint.

Use when

  • the evidence base is stable enough for a final recommendation
  • the writing line is sufficiently complete
  • the user asked for a final summary or closure
  • the quest should be paused or archived with a clean state

Do not use when

  • major evidence gaps are still unresolved
  • the current line obviously needs another experiment or analysis pass
  • the quest is still in exploratory ideation

Preconditions and gate

Before finalizing, gather:

  • latest baseline state
  • latest accepted run and analysis state
  • latest writing state
  • latest decisions and open blockers
  • latest quest documents
  • latest review / proofing / submission state when a paper bundle exists
  • the paper bundle manifest and its referenced paths when the quest has a paper-like deliverable
  • the paper evidence ledger and selected-outline section statuses when the quest has a paper-like deliverable

If finalization reveals that the quest is still too uncertain, route back through decision rather than forcing closure. For paper-like deliverables, do not finalize while any of these remain true:

  • required main-text outline items are still unresolved
  • completed analysis remains unmapped into the paper contract
  • the active paper line still reports open supplementary work that is expected to block the manuscript

If the current paper-state blocker is not obvious from the existing files, call artifact.get_paper_contract_health(detail='full') before deciding whether finalize is legitimate. If the active quest/runtime state is unclear after restart or long pause, call artifact.get_quest_state(detail='summary') first. If the exact latest SUMMARY.md, status.md, or active user requirement wording matters for closure, call artifact.read_quest_documents(...). If earlier user/assistant continuity matters for whether the quest should really stop, call artifact.get_conversation_context(...) instead of guessing from prompt context alone.

Truth sources

Use:

  • SUMMARY.md
  • latest decisions
  • baseline artifacts
  • run artifacts
  • analysis reports
  • writing outputs
  • review, proofing, and submission outputs when they exist
  • Git history and graph
  • durable literature notes already produced during the quest
  • outputs or notes gathered through artifact.arxiv(...) when final claim checks require rereading an arXiv paper

Do not finalize from chat memory alone.

Required durable outputs

The finalize stage should usually leave behind:

  • refreshed SUMMARY.md
  • refreshed status.md
  • final report artifact
  • final decision artifact
  • refreshed Git graph
  • explicit limitations and next-step recommendation
  • a final claim ledger or equivalent claim-status summary
  • a compact resume packet or handoff packet when later continuation is plausible

If the quest produced a paper-style bundle, finalization should also check that the writing stage left behind enough closure evidence, such as:

  • selected outline and outline selection records
  • evidence ledger records and section-level result tables
  • review output
  • proofing output
  • submission or packaging checklist
  • final draft or bundle manifest

Workflow

1. Consolidate the accepted evidence and package inventory

State clearly:

  • accepted baseline
  • strongest supported claims
  • weaker or partial claims
  • important negative results
  • unresolved risks
  • key deliverables that exist and where they live

Do not only say that evidence exists. Say clearly what exists and why it matters. Name concrete paths or artifact ids only when the user asks for them or needs them to act. When a paper bundle exists, verify the manifest inventory explicitly, including:

  • paper/paper_bundle_manifest.json
  • paper/evidence_ledger.json
  • the recorded paper_branch and source evidence branch / run fields in that manifest
  • referenced outline_path
  • referenced draft_path
  • referenced writing_plan_path
  • referenced references_path
  • referenced claim_evidence_map_path
  • referenced evidence_ledger_path
  • referenced baseline_inventory_path
  • referenced compile_report_path
  • referenced pdf_path
  • referenced latex_root_path
  • release/open_source/manifest.json when open-source preparation has started
  • release/open_source/cleanup_plan.md when the paper line is being prepared for a public code release
2. Build the final claim ledger

For every important outcome, classify it as one of:

  • supported
  • partially supported
  • unsupported
  • deferred

For each claim, record:

  • claim text or claim id
  • evidence paths
  • key caveats
  • whether it is safe to surface in summaries or papers

If a claim was once believed and later weakened, preserve that downgrade history rather than silently deleting it.

Also build a compact belief-change log for the most important claim transitions, such as:

  • supported -> partial
  • partial -> unsupported
  • promising route -> abandoned
  • draft-ready -> evidence-gap

For each transition, record:

  • what changed
  • which evidence caused the change
  • what the new recommendation is
3. Produce a final limitations and failure section

Limitations should include:

  • data or split limitations
  • metric limitations
  • implementation limitations
  • robustness limitations
  • reproducibility risks
  • claims intentionally not made

Also preserve:

  • failed branches that meaningfully changed the research direction
  • blocked items that remain unresolved
  • confounders or comparability issues that weaken confidence
  • handoff cautions for anyone resuming the quest later
Show full SKILL.md (656 more words)Show less
4. Produce the final recommendation

Choose the most honest next recommendation, such as:

  • stop and archive
  • stop and publish
  • continue later with a targeted experiment
  • continue later with a targeted analysis campaign
  • reset the current line and revisit ideation

The recommendation should include:

  • the chosen action
  • why that action is appropriate now
  • what evidence most strongly supports it
  • what would have to become true to justify a different recommendation

When deciding whether the quest is publish-ready or only archive-ready, be explicit about which writing or validation gates have actually passed.

5. Build a resume or handoff packet

If the quest may continue later, leave behind a compact restart packet that answers:

  • where the strongest evidence is
  • what the current accepted baseline is
  • what the current preferred route is
  • what the top blockers are
  • what should be read first on resume
  • what should not be repeated

This packet should be short, high-signal, and directly usable by a future agent turn.

6. Refresh the durable quest view

Refresh:

  • SUMMARY.md
  • status.md
  • Git graph export

If the summary changes materially, make it clear why the quest is now considered final or paused.

When summarizing long histories, prefer the highest-impact findings and decisions rather than a full chronological replay.

7. Record the final decision

The final stage should end with an explicit durable decision or report rather than an implied stopping point. If multiple closure options were available, record why the chosen one beat the alternatives.

Finalization-quality rules

Good finalization:

  • distinguishes supported findings from hopes
  • preserves negative evidence
  • names open questions honestly
  • leaves a clean state for later resumption
  • exposes whether writing/proofing/submission gates passed or failed
  • makes reopen conditions explicit

Weak finalization:

  • overclaims unresolved work
  • hides failed branches
  • skips limitations
  • leaves no clear recommendation
  • claims “done” without showing what is actually done
  • drops the package or file inventory needed for resumption
  • ignores unmapped completed analysis that never entered the paper contract

Memory rules

Stage-start requirement:

  • begin every finalize pass with memory.list_recent(scope='quest', limit=5)
  • then run at least one finalize-relevant memory.search(...) before closure writing
  • if several idea, run, or campaign lines exist, retrieve only the memory tied to the line being finalized unless the final report is explicitly comparing lines

Finalize should read memory before writing closure, especially:

  • quest decisions
  • quest knowledge
  • quest episodes
  • quest papers when the final story depends on citation or literature context

If final closure depends on rereading a paper, keep the same split:

  • use web search only to relocate or verify the paper reference
  • use artifact.arxiv(paper_id=..., full_text=False) for the actual paper reading or refresh
  • switch to full_text=True only when the shorter view is insufficient

Write to memory only when the lesson is reusable across quests, such as:

  • general methodological pitfalls
  • robust baseline lessons
  • durable writing or evaluation lessons

Stage-end requirement:

  • if finalize produced a durable cross-quest lesson worth reusing later, write at least one memory.write(...) before leaving the stage

Quest-specific closure state belongs in files and artifacts first, not only memory.

Artifact rules

Typical final artifacts:

  • report artifact summarizing final state
  • decision artifact indicating stop, archive, or continue-later recommendation
  • graph artifact via artifact.render_git_graph()

Good final artifacts often include:

  • a final report focused on supported findings, limitations, and packaging state
  • a final decision with action, reasons, and reopen conditions
  • a graph export when the path through the quest matters for later resumption
  • a milestone only when a human-facing checkpoint helps

Failure and blocked handling

If finalization is premature, record that explicitly.

Common blocked finalize states:

  • unresolved_major_claim
  • unresolved_write_gate
  • missing_proofing_or_submission_checks
  • unclear_final_recommendation
  • missing_handoff_packet
  • stale_summary_or_graph
  • unresolved_package_inventory

In that case, route back to the proper stage through decision.

Extra references

Use these references when you need a denser closure checklist:

  • references/finalization-checklist.md
  • references/resume-packet-template.md

Exit criteria

Exit the finalize stage once one of the following is durably true:

  • a final or pause-ready summary exists
  • the graph is refreshed
  • the limitations and recommendation are explicit
  • the stopping point is recorded through artifact
  • the claim ledger and package inventory are clear enough for later resumption or publication handoff

© OpenLAIR, 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 2 other files (references) in skills/ds-finalize of OpenLAIR/dr-claw.

  • SKILL.md
  • references/finalization-checklist.md
  • references/resume-packet-template.md

Open the folder on GitHubat commit d51b64e

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Questions about Ds Finalize

What does Ds Finalize do?

A skill your agent uses when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving. Ds Finalize is an agent skill from OpenLAIR/dr-claw. Use when the quest is ready to consolidate final claims, limitations, recommendations, summary state, and graph exports before stopping or archiving.

When should I use Ds Finalize?

Ds Finalize fits situations like: the quest is ready to consolidate final claims; recommendations; graph exports before stopping.

How do I install Ds Finalize in Claude Code?

Run `npx skills add OpenLAIR/dr-claw --skill ds-finalize -a claude-code`. Or copy the skill folder (skills/ds-finalize in OpenLAIR/dr-claw) into .claude/skills/ds-finalize in your project. Claude Code loads it when a task matches its description.

How do I install Ds Finalize in Codex?

Run `npx skills add OpenLAIR/dr-claw --skill ds-finalize -a codex`. Or copy the skill folder (skills/ds-finalize in OpenLAIR/dr-claw) into .agents/skills/ds-finalize in your project. Codex loads it when a task matches its description.

Can I use Ds Finalize 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 OpenLAIR/dr-claw --skill ds-finalize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ds-finalize, .gemini/skills/ds-finalize, .github/skills/ds-finalize and .opencode/skills/ds-finalize in your project.

What does Ds Finalize need to run?

SKILL.md names no scripts, command-line tools or credentials: Ds Finalize is instructions for the agent only.

Does Ds Finalize 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 Ds Finalize 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. Review the folder before installing.

What licence does Ds Finalize use?

Ds Finalize is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ds Finalize use?

About 3.2k tokens (SKILL.md is roughly 13k 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 555 tokens, read only when the agent opens those files.

What are the alternatives to Ds Finalize?

Skills that share tags, products or a category with Ds Finalize: Claims (ruvnet/ruflo, 74k stars), Implementing API Abuse Detection With Rate Limiting (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Web3 Rate Limiting Circuit Breaker (sickn33/agentic-awesome-skills, 47k stars) and Limits (parcadei/Continuous-Claude-v3, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ds Finalize?

OpenLAIR (a GitHub organization) maintains it in OpenLAIR/dr-claw, which has 1,153 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on September 17, 2026.

Source: OpenLAIR/dr-claw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.