Agent skill

Decision Logger

by borghei in borghei/Claude-Skills

Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus.

MITAuto-check passed

Install Decision Logger

skills CLI
$ npx skills add borghei/Claude-Skills --skill decision-logger -a claude-code

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

GitHub CLI
$ gh skill install borghei/Claude-Skills decision-logger --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/c-level-advisor/decision-logger .claude/skills/decision-logger && 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
decision-logger
GitHub stars
874
Token cost
~4.8k tokens
SKILL.md length
1,593 words
Files
4 (incl. scripts)
Skills in repo
364
Repo updated
First seen
Licence
MIT

At a glance

Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus.

  • Works in 3 steps: decision_tracker.py → decision_quality_scorer.py → decision_tree_builder.py
  • Logging decisions
  • SKILL.md covers Keywords, Two-Layer Architecture, Decision Entry Format and Conflict Detection System, plus 8 more sections
  • Runs Python scripts from its folder; calls python

What it does

Decision Logger is an agent skill from borghei/Claude-Skills. Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus. Use when logging decisions, reviewing past decisions, or checking overdue action items.

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/decision_quality_scorer.py`, `scripts/decision_tracker.py` and `scripts/decision_tree_builder.py`).

The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Logging decisions
  • Reviewing past decisions
  • Checking overdue action items

Example prompts

  • “/decision-logger”

Requirements

  • Python 3

Workflow steps

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

  1. decision_tracker.py
  2. decision_quality_scorer.py
  3. decision_tree_builder.py

What it can do on your machine

Read from SKILL.md and the folder at commit c9a1487. 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/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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

Decision Logger loads about 4.8k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 1,593 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit c9a1487, republished under its MIT licence (© borghei). 1,593 words, ~4,791 tokens.

Download SKILL.mdSave it as .claude/skills/decision-logger/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
decision-logger
description
Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus. Use when logging decisions, reviewing past decisions, or checking overdue action items.
license
MIT + Commons Clause
metadata.version
2.0.0
metadata.author
borghei
metadata.category
c-level
metadata.domain
decision-memory
metadata.updated
2026-03-09
metadata.frameworks
two-layer-memory, conflict-detection, supersession-tracking, action-item-management, decision-search
metadata.triggers
decision log, log decision, past decisions, decision history, action items, overdue items, decision review, decision conflict, decision tracking, board…

Decision Logger

Two-layer memory system for executive decisions. Layer 1 stores everything discussed. Layer 2 stores only what the founder approved. Future sessions read Layer 2 only -- this prevents hallucinated consensus from past debates bleeding into new deliberations.

Keywords

decision log, memory, approved decisions, action items, board minutes, conflict detection, DO_NOT_RESURFACE, decision history, overdue, supersession, decision search, decision tracking, accountability


Two-Layer Architecture

Why Two Layers?

Single-layer decision logs create a dangerous problem: agents read old debates, rejected proposals, and discarded ideas, then treat them as context for new decisions. This causes "hallucinated consensus" where rejected ideas gradually become accepted through repetition.

The two-layer system prevents this by strictly separating raw discussion from approved decisions.

Layer Architecture
Layer 1: Raw Transcripts (NEVER auto-loaded)
  Location: memory/board-meetings/YYYY-MM-DD-raw.md
  Contains: Full deliberation, all perspectives, rejected arguments
  Loaded: Only on explicit founder request
  Retention: Active 90 days, then archived

Layer 2: Approved Decisions (AUTO-LOADED every session)
  Location: memory/board-meetings/decisions.md
  Contains: Only founder-approved decisions and action items
  Loaded: Automatically at start of every board meeting (Phase 1)
  Mutation: Append-only. Decisions are never deleted, only superseded.
Layer Interaction Rules
RuleRationale
Layer 2 is append-onlyPreserves complete decision history
Layer 1 is never auto-loadedPrevents hallucinated consensus
Only Chief of Staff writes to Layer 2Single point of control
Agents never write directlyAll writes go through Chief of Staff after founder approval
Superseded decisions stay in Layer 2History is the record; nothing is deleted

Decision Entry Format

Standard Decision Record
markdown
## [YYYY-MM-DD] -- [DECISION TITLE]

**Decision:** [One clear statement of what was decided]
**Context:** [1-2 sentences on why this decision was needed]
**Owner:** [One person or role accountable for execution]
**Deadline:** [YYYY-MM-DD]
**Review Date:** [YYYY-MM-DD]
**Confidence:** [High / Medium / Low]
**Rationale:** [Why this option over alternatives, 1-2 sentences]

**User Override:** [If founder changed agent recommendation -- what and why]

**Rejected Alternatives:**
- [Proposal] -- [reason for rejection] [DO_NOT_RESURFACE]
- [Proposal] -- [reason for rejection]

**Action Items:**
- [ ] [Action] -- Owner: [name] -- Due: [YYYY-MM-DD]
- [ ] [Action] -- Owner: [name] -- Due: [YYYY-MM-DD]

**Dependencies:** [Other decisions this depends on]
**Supersedes:** [DATE of previous decision on same topic, if any]
**Superseded by:** [Filled retroactively if overridden later]
**Raw transcript:** memory/board-meetings/[DATE]-raw.md
**Tags:** [topic tags for search -- e.g., pricing, hiring, market-entry]
Completed Action Item Format
markdown
- [x] [Action] -- Owner: [name] -- Completed: [YYYY-MM-DD] -- Result: [one sentence]

Conflict Detection System

Before logging any new decision, the system checks for three types of conflicts.

Conflict Type 1: DO_NOT_RESURFACE Violation

A new decision matches a previously rejected proposal.

Detection: New proposal text similarity > 70% to a rejected proposal

Response:
  BLOCKED: "[Proposal]" was rejected on [DATE].
  Reason: [original rejection reason]

  To reopen: Founder must explicitly say "reopen [topic] from [DATE]"
  This cannot be overridden by agents.
Conflict Type 2: Topic Contradiction

Two active decisions on the same topic reach different conclusions.

Detection: Same tags + contradictory conclusions

Response:
  DECISION CONFLICT DETECTED

  Active decision (older): [DATE] -- [decision text]
  New decision: [DATE] -- [decision text]

  These decisions contradict each other.

  Options:
  1. Supersede old decision (new replaces old)
  2. Merge decisions (reconcile the conflict)
  3. Defer to founder (present both, let founder choose)
Conflict Type 3: Owner Conflict

Same action assigned to different people in different decisions.

Detection: Same action description, different owners

Response:
  OWNER CONFLICT

  Action: "[action text]"
  Decision 1 ([DATE]): Owner = [Person A]
  Decision 2 ([DATE]): Owner = [Person B]

  Resolve: Which owner is correct?
Conflict Resolution Decision Tree
START: Conflict detected
  |
  v
[What type of conflict?]
  |
  +-- DO_NOT_RESURFACE --> Block automatically. Only founder can reopen.
  |
  +-- Topic contradiction --> [Is the new decision from a board meeting?]
  |                           |
  |                           +-- YES --> Supersede old by default (board > individual)
  |                           +-- NO  --> Present both to founder for resolution
  |
  +-- Owner conflict --> [Which decision is more recent?]
                         |
                         +-- Flag to founder with both dates
                         +-- Default to more recent unless founder overrides

Decision Lifecycle

States
PROPOSED --> APPROVED --> ACTIVE --> [COMPLETED | SUPERSEDED | EXPIRED]

PROPOSED:    Agent synthesis presented to founder
APPROVED:    Founder explicitly approved
ACTIVE:      Being executed, action items in progress
COMPLETED:   All action items done, review confirmed success
SUPERSEDED:  New decision replaced this one
EXPIRED:     Review date passed without renewal
State Transitions
FromToTriggerWho
ProposedApprovedFounder says "yes" or "approve"Founder
ProposedRejectedFounder says "no" or "reject"Founder
ApprovedActiveAction items begin executionAutomatic
ActiveCompletedAll action items marked doneChief of Staff
ActiveSupersededNew decision on same topicChief of Staff
ActiveExpiredReview date passed, no renewalSystem alert

Clarify First

Before logging a decision, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • The exact decision statement (one clear sentence of what was decided) — this is the heart of the record; a vague statement makes the log useless for future conflict detection
  • Owner and deadline — every decision record needs a single accountable person and a date, or it cannot be tracked or surfaced as overdue
  • Rejected alternatives and why — these become DO_NOT_RESURFACE entries that prevent rejected ideas from re-entering future deliberations
  • Whether this supersedes a prior decision on the same topic — drives conflict detection and supersession tracking against the existing log

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Logging Workflow

Post-Decision Logging (after Board Meeting Phase 5)
Step 1: Founder approves synthesis
  |
Step 2: Write Layer 1 raw transcript
  --> memory/board-meetings/YYYY-MM-DD-raw.md
  |
Step 3: Run conflict detection against decisions.md
  |
  +-- Conflicts found --> Surface to founder, wait for resolution
  +-- No conflicts --> Continue
  |
Step 4: Append approved entries to decisions.md (Layer 2)
  |
Step 5: Set review dates and action item deadlines
  |
Step 6: Confirm to founder:
  "Logged: [N] decisions, [M] action items tracked, [K] flags added"

Action Item Management

Overdue Detection

At the start of every session, scan for:

  1. Action items past their deadline
  2. Decisions with review dates that have passed
  3. Decisions older than 90 days with no completion status
Alert Format
OVERDUE ITEMS (as of [today's date])

Action Items Past Deadline:
  1. [Action] -- Owner: [name] -- Due: [date] -- [X] days overdue
     From decision: [decision title] ([date])

  2. [Action] -- Owner: [name] -- Due: [date] -- [X] days overdue

Decisions Pending Review:
  1. [Decision title] -- Review was due: [date]
     Original decision: [summary]
     Prompt: "You decided [X] on [date]. Worth a check-in?"

Stale Decisions (> 90 days, no status update):
  1. [Decision title] -- Decided: [date] -- Last update: [date]
Action Item Priority Matrix
UrgencyImpactPriorityResponse
OverdueHighCriticalEscalate to founder immediately
OverdueLowHighFlag in next session
Due this weekHighHighSurface proactively
Due this weekLowMediumInclude in weekly summary
Due next monthAnyLowMonitor only

Search and Retrieval

Search Capabilities
Query TypeExampleReturns
By topic"pricing"All decisions tagged with pricing
By owner"CTO"All decisions and actions owned by CTO
By date range"Q4 2025"All decisions from Oct-Dec 2025
By status"overdue"All overdue action items
By conflict"conflicts"All detected contradictions
By tag"hiring AND engineering"Intersection of tags
Decision Summary Views
ViewContentsWhen Used
Last 10Most recent 10 approved decisionsDefault quick view
Full historyAll decisions, chronologicalAudit or deep review
By ownerGrouped by accountable personAccountability check
By topicGrouped by tagStrategic review
Overdue onlyOnly overdue itemsAction management
Active onlyOnly decisions with open action itemsExecution tracking

File Structure

memory/
  board-meetings/
    decisions.md           # Layer 2: append-only, founder-approved
    YYYY-MM-DD-raw.md      # Layer 1: full transcript per meeting
    archive/
      YYYY/                # Raw transcripts after 90 days

Integration with Other Skills

SkillIntegration Point
Chief of Staff (chief-of-staff)Manages the logging workflow, writes to Layer 2
Board Meeting (board-meeting)Triggers logging after Phase 5 approval
Strategic Alignment (strategic-alignment)Checks if decisions cascade properly to team goals
Executive Mentor (executive-mentor)Reviews stale decisions for re-evaluation
Org Health (org-health-diagnostic)Decision velocity as health indicator

Red Flags

  • Same topic discussed 3+ times without a logged decision -- decision avoidance
  • Action items consistently overdue by the same owner -- capacity or accountability issue
  • Decisions made without checking history -- risk of contradiction
  • Layer 1 being loaded without explicit request -- hallucinated consensus risk
  • No review dates set on decisions -- decisions age without re-evaluation
  • Rejected proposals resurfacing in new language -- DO_NOT_RESURFACE not enforced
  • Decision log not consulted at start of board meetings -- institutional memory not used
  • All decisions owned by one person -- bottleneck or delegation failure

Proactive Triggers

  • Review date passed on a decision -- prompt: "You decided [X] on [date]. Worth checking in?"
  • Action item overdue > 7 days -- escalate to founder with owner context
  • Same topic area has 3+ active decisions -- consolidation review needed
  • 30+ days without any logged decision -- is the system being used?
  • New decision proposed that matches DO_NOT_RESURFACE -- block and explain
  • Decision from 6+ months ago with no status update -- mark as stale, prompt review

Output Artifacts

RequestDeliverable
"Show recent decisions"Last 10 approved decisions with status
"What's overdue?"All overdue action items with owner and days past due
"Search decisions about [topic]"Filtered decision history by topic/tag
"Log this decision"Formatted decision entry with all fields
"Check for conflicts"Conflict scan against all active decisions
"Decision summary for board"Decision velocity, completion rate, open items

Tool Reference

Show full SKILL.md (661 more words)Show less
1. decision_tracker.py

Tracks executive decisions with full lifecycle management (Proposed > Approved > Active > Completed/Superseded/Expired). Scans for overdue action items, stale decisions, and generates status summaries.

bash
python scripts/decision_tracker.py --input decisions.json --json
python scripts/decision_tracker.py --input decisions.json
FlagTypeDescription
--inputrequiredPath to JSON file with decision records (title, status, owner, deadline, action items, tags)
--jsonoptionalOutput in JSON format instead of human-readable text
2. decision_quality_scorer.py

Scores decision quality across 6 dimensions: framing (problem definition), alternatives (options considered), information (evidence quality), reasoning (logic soundness), commitment (action clarity), and metacognition (awareness of uncertainty). Generates improvement recommendations.

bash
python scripts/decision_quality_scorer.py --input decision_assessments.json --json
python scripts/decision_quality_scorer.py --input decision_assessments.json
FlagTypeDescription
--inputrequiredPath to JSON file with decision assessments (dimension scores 1-10, optional outcome data)
--jsonoptionalOutput in JSON format instead of human-readable text
3. decision_tree_builder.py

Builds decision trees with expected value analysis. Calculates optimal paths through probability-weighted outcomes, identifies highest-value decisions, and generates sensitivity analysis on key assumptions.

bash
python scripts/decision_tree_builder.py --input tree_data.json --json
python scripts/decision_tree_builder.py --input tree_data.json
FlagTypeDescription
--inputrequiredPath to JSON file with decision nodes (options, probabilities, outcomes, values)
--jsonoptionalOutput in JSON format instead of human-readable text

Troubleshooting

ProblemLikely CauseResolution
Same topic discussed 3+ times without a logged decisionDecision avoidance or no clear decision-making authorityForce a decision at next session; use decision tree builder to clarify options; assign explicit decision owner
Action items consistently overdue by same ownerOwner over-committed, lacks capacity, or accountability issueReview owner workload; redistribute if capacity issue; escalate to founder if accountability issue
Decisions made without checking historyDecision log not consulted at session start; no integration habitAutomate decision log loading at board meeting Phase 1; surface relevant past decisions proactively
Rejected proposals resurfacing in new languageDO_NOT_RESURFACE not enforced; team members unaware of prior rejectionEnforce conflict detection before logging; block proposals matching rejected items; require explicit "reopen" from founder
Decision log growing but never consulted for patternsLog treated as archive, not strategic toolRun quarterly decision review; analyze decision velocity, completion rate, and quality trends
All decisions owned by one personBottleneck or delegation failureDistribute ownership; use decision quality scorer to assess whether centralization improves or hurts quality
Decision quality scores low on "alternatives" dimensionTeam anchoring on first option instead of exploringRequire minimum 3 alternatives for decisions above a threshold; use decision tree builder to model options

Success Criteria

  • All board meeting decisions logged in Layer 2 within 24 hours of approval
  • Action item completion rate exceeds 80% within stated deadlines
  • Zero DO_NOT_RESURFACE violations (rejected proposals do not re-enter decision flow)
  • Decision review dates honored for 90%+ of active decisions
  • Decision quality score averages above 7/10 across all 6 dimensions
  • Conflict detection catches 100% of topic contradictions before new decisions are logged
  • Decision log consulted at the start of every board meeting session

Scope & Limitations

In scope: Two-layer decision memory architecture, decision entry and lifecycle management (Proposed > Approved > Active > Completed/Superseded/Expired), conflict detection (DO_NOT_RESURFACE, topic contradiction, owner conflict), action item tracking with overdue alerting, decision search and retrieval by topic/owner/date/status, decision quality scoring, and expected value analysis via decision trees.

Out of scope: CRM or project management tool integration (tools consume JSON exports), meeting transcription or recording, team-level task management (use project-management/ skills), strategic planning or OKR tracking (use strategic-alignment or ceo-advisor), and automated decision-making. This skill tracks and evaluates decisions; it does not make them.

Limitations: Conflict detection uses tag and text matching; semantically similar but differently worded proposals may not be caught. Decision quality scoring is retrospective and depends on honest self-assessment. Decision tree expected value calculations assume probabilities are estimable; highly uncertain environments may make probability assignment misleading. The two-layer architecture requires discipline to maintain; if Layer 2 is not consistently updated, institutional memory degrades.


Integration Points

  • chief-of-staff -- Manages the logging workflow; single point of control for Layer 2 writes
  • board-meeting -- Triggers decision logging after Phase 5 approval; decision log loaded at Phase 1
  • strategic-alignment -- Checks if decisions cascade properly to team goals and OKRs
  • executive-mentor -- Reviews stale decisions for re-evaluation; coaches on decision quality improvement
  • ceo-advisor -- Strategic decisions logged and tracked; decision patterns inform leadership coaching

© borghei, 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 3 other files (scripts) in c-level-advisor/decision-logger of borghei/Claude-Skills.

  • SKILL.md
  • scripts/decision_quality_scorer.py
  • scripts/decision_tracker.py
  • scripts/decision_tree_builder.py

Open the folder on GitHubat commit c9a1487

Compare with similar skills

Decision Logger 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.

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Executionalsk1992/CloddsBot2.9k—~1.7kAutomated safety check: PassMIT
Executive Mentoralirezarezvani/claude-skills28k1 repos~1.8kAutomated safety check: PassMIT

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Questions about Decision Logger

What does Decision Logger do?

Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus. Decision Logger is an agent skill from borghei/Claude-Skills. Two-layer memory for executive decisions, separating raw deliberation from approved decisions to prevent hallucinated consensus.

When should I use Decision Logger?

Decision Logger fits situations like: logging decisions; reviewing past decisions; checking overdue action items.

How do I install Decision Logger in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill decision-logger -a claude-code`. Or copy the skill folder (c-level-advisor/decision-logger in borghei/Claude-Skills) into .claude/skills/decision-logger in your project. Claude Code loads it when a task matches its description.

How do I install Decision Logger in Codex?

Run `npx skills add borghei/Claude-Skills --skill decision-logger -a codex`. Or copy the skill folder (c-level-advisor/decision-logger in borghei/Claude-Skills) into .agents/skills/decision-logger in your project. Codex loads it when a task matches its description.

Can I use Decision Logger 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 borghei/Claude-Skills --skill decision-logger -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/decision-logger, .gemini/skills/decision-logger, .github/skills/decision-logger and .opencode/skills/decision-logger in your project.

What does Decision Logger need to run?

Going by SKILL.md and its folder, Decision Logger needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Decision Logger 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 Decision Logger 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 Decision Logger use?

Decision Logger 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 Decision Logger use?

About 4.8k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Decision Logger?

Skills that share tags, products or a category with Decision Logger: Execute (alirezarezvani/claude-skills, 28k stars), Ulw Execute (code-yeongyu/oh-my-openagent, 70k stars), Execute (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars) and Execution (alsk1992/CloddsBot, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Decision Logger?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 874 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 7, 2026.

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