fix(kyberforge): bridge apm content to Claude Code's flat plugin discovery
Claude Code's (and Copilot's) native plugin installer has zero awareness of .apm/ nesting -- it convention-scans only flat skills/, agents/, commands/, hooks.json at each plugin's root. Confirmed via strings on the installed claude binary and live installs of git@holocron/gitea@holocron/kyberforge@ holocron, all reporting Skills(0) Agents(0) Hooks(0) post ADR-0015's apm conversion. Root cause (apm_cli/core/plugin_manifest.py): apm's plugin.json compiler deliberately strips skills/agents/commands keys, assuming the host already auto-discovers those convention directories -- it has no model of .apm/ being host-visible at all. Separately, apm's own bundle exporter (apm_cli/bundle/plugin_exporter.py, behind `apm pack --format plugin`) implements the correct .apm/ -> flat mapping, but only ever targeted build/<name>-<version>/, a path nothing in marketplace.json's source: points at. scripts/sync-plugin-content.sh wraps that bundle exporter and copies its agents/, skills/, commands/, instructions/, extensions/, and merged hooks.json back into each plugin's own root as a second tracked compiled-output category -- same governance status as .claude-plugin/plugin.json: generated from .apm/, never hand-edited. tests/ subdirectories are excluded from the mirror (dev fixtures, not host-visible runtime content; several hardcode a relative repo-root walk-up sized for the .apm/-nested depth, which breaks when duplicated one level shallower). Applied for real across all 6 plugins and verified two ways: `claude plugin validate --strict` passes on every real plugin directory, and a live `claude --plugin-dir <path> -p "list skills/agents"` behavioral test confirms content is now actually discovered. Also, from the same issue #90 review round: - scripts/check-manifests.sh pointed at each plugin's root-level plugin.json (checking skills/hooks/mcpServers/agents pointer fields) -- that file was a stale near-duplicate of .claude-plugin/plugin.json nothing else read or wrote, now deleted across all 6 plugins. check-manifests.sh is rewritten to validate .claude-plugin/plugin.json instead, and drops the pointer-field checks entirely (nothing to check -- those fields are correctly absent by design). Content-presence drift is now check-plugin-content-sync's job, a new pre-push hook wired in .pre-commit-config.yaml. docs/adr/0017 records the root cause and decision in full, including two rejected alternatives (patching plugin.json's path fields directly -- apm's compiler strips them on every run; pointing marketplace.json at apm pack's build/ output -- a version-suffixed non-source directory nothing can install from without an extra build step). ADR-0015 and CONTEXT.md are updated to point at it. Refs: #90
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---
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source_keys:
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- agentskills-spec
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- agentskills-best-practices
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---
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# Body Discipline Reference
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Source: agentskills.io — skill-authoring
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## The core test
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For every sentence in the body, ask: **"Would the agent get this wrong without this instruction?"**
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If no — cut it. The agent already knows it from general training. Adding it wastes tokens and dilutes the signal of what matters.
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## What belongs in the body
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Include content the agent lacks:
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- Project-specific conventions and domain procedures it cannot infer
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- Non-obvious edge cases and environment-specific gotchas
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- The specific tools or sequences to use (not the full range of options)
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- One default per decision point with one escape hatch
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Do not include:
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- Concepts the agent already knows (what JSON is, how HTTP works, what a CSV is)
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- Exhaustive option lists — pick a default; the agent doesn't benefit from choosing
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- Steps the agent handles independently — over-specifying leads to unproductive paths
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- Restatements of the description — it's already in context
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## Calibrating control
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**Be prescriptive** when operations are fragile, consistency matters, or a specific sequence must be followed:
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```markdown
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Run exactly:
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\`\`\`bash
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python scripts/migrate.py --verify --backup
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\`\`\`
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Do not modify the command or add additional flags.
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```
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**Give freedom** when multiple approaches are valid. Explaining *why* outperforms rigid directives — agents make better decisions when they understand the purpose.
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## Defaults not menus
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Never present a list of equivalent options — pick one and mention the alternative briefly:
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```markdown
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# Too many options
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Use pypdf, pdfplumber, PyMuPDF, or pdf2image...
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# Default with escape hatch
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Use pdfplumber for text extraction. For scanned PDFs requiring OCR, use pdf2image instead.
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```
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## Gotchas sections
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Highest value content — environment-specific facts that defy reasonable assumptions. Place near the top of the body so the agent reads them before encountering the situation.
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```markdown
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## Gotchas
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- The `users` table uses soft deletes. Always include `WHERE deleted_at IS NULL`.
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- User ID is `user_id` in the database, `uid` in auth, `accountId` in billing. Same value.
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```
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Each entry must be a specific, surprising fact — not a general tip or reminder.
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## Progressive disclosure
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Keep `SKILL.md` under 500 lines. When more content is needed, move it to `references/` and load conditionally:
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```markdown
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If the API returns a non-200 status, read `references/api-errors.md`.
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```
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"If X, read Y" is more useful than "see references/ for details." The agent loads on demand rather than up front.
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## Auditing guidance
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Flag as FAIL if:
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- A sentence answers "no" to the core test (would agent get this wrong without it?) — it is padding
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- Decision points present a menu of options with no default
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- Instructions repeat content already in the description
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- Prescriptive sequences are used where flexibility is fine, or vice versa
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Flag as SUGGESTION if:
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- A rationale is missing from an include/exclude rule (present but unexplained)
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- Gotchas are correct but placed late in the body rather than near the top
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- A conditional reference trigger is vague ("see references/") rather than specific ("If X, read Y")
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---
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source_keys:
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- agentskills-spec
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- agentskills-optimizing-descriptions
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---
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# Description Quality Reference
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Source: agentskills.io — optimizing-descriptions
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## How triggering works
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At startup, agents load only the `name` and `description` of each skill. When a user's task matches a description, the agent reads the full `SKILL.md` into context. **The description carries the entire triggering burden** — the body is never seen until after triggering.
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Agents typically consult skills only for tasks requiring knowledge beyond their defaults. Specialized knowledge — unfamiliar APIs, domain-specific workflows, uncommon formats — is where description wording makes the difference.
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## What a good description does
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- **Imperative phrasing** — "Use when..." not "This skill does...". The agent is deciding whether to act.
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- **User intent, not mechanics** — describe what the user is trying to achieve, not how the skill works internally.
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- **Err toward being pushy** — explicitly name contexts where the skill applies, including cases where the user doesn't name the domain: "even if they don't mention X explicitly."
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- **Specificity over vagueness** — "parses and validates OpenAPI specs" beats "helps with APIs."
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- **Near-miss exclusions** — add "Do not use when..." only if a near-miss skill exists that could steal activations. Use strong near-misses (queries that share keywords but need something different), not weak ones ("write a fibonacci function").
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- **Hard limit: 1024 characters** — descriptions grow during revision; check length before finalising.
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## Before / after
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```yaml
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# Weak
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description: Process CSV files.
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# Strong
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description: >
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Analyze CSV and tabular data files — compute summary statistics,
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add derived columns, generate charts, and clean messy data. Use when
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the user has a CSV, TSV, or Excel file and wants to explore, transform,
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or visualize the data, even if they don't explicitly mention "CSV" or
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"analysis."
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```
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The strong version names capabilities precisely and broadens applicability beyond explicit keyword matches.
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## Auditing guidance
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Flag as FAIL if:
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- Phrasing is descriptive ("This skill...") not imperative ("Use when...")
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- Capabilities are vague ("helps with APIs") — require precise verbs and nouns
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- No indirect trigger coverage when indirect cases clearly exist
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- No near-miss exclusions when a sibling skill could plausibly steal activations
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- Length exceeds 1024 characters
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Flag as SUGGESTION if:
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- Indirect trigger coverage exists but could be more specific
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- Near-miss exclusions are present but target weak near-misses only
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59
plugins/kyberforge/skills/skill-audit/references/sources.md
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59
plugins/kyberforge/skills/skill-audit/references/sources.md
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# Sources
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<!-- agentskills.io/llms.txt was used for initial source discovery and is not listed below; it contributed no skill file content directly. -->
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## agentskills-home
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- **URL:** https://agentskills.io/home.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Agent Skills overview — what it is, why it exists, progressive disclosure model, ecosystem of 35+ implementing tools
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- **Contributing files:** SKILL.md
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- **Status:** `extracted`
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## agentskills-spec
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- **URL:** https://agentskills.io/specification.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Complete SKILL.md format specification — frontmatter fields, constraints, body content, optional directories, progressive disclosure levels, file references, validation
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- **Contributing files:** SKILL.md, references/body-discipline.md, references/description-quality.md
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- **Status:** `extracted`
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## agentskills-best-practices
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- **URL:** https://agentskills.io/skill-creation/best-practices.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Best practices for skill creators — starting from real expertise, spending context wisely, calibrating control, instruction patterns (gotchas, templates, checklists, validation loops)
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- **Contributing files:** SKILL.md, references/body-discipline.md
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- **Status:** `extracted`
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## agentskills-optimizing-descriptions
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- **URL:** https://agentskills.io/skill-creation/optimizing-descriptions.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** How to systematically test and improve skill descriptions for triggering accuracy — eval queries, trigger rate testing, train/validation splits, optimization loop
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- **Contributing files:** SKILL.md, references/description-quality.md
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- **Status:** `extracted`
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## agentskills-evaluating-skills
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- **URL:** https://agentskills.io/skill-creation/evaluating-skills.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Eval-driven skill quality improvement — test case design, workspace structure, assertion writing, grading, benchmarking, human review, iteration loop
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- **Contributing files:** (none — eval workflow not directly informing audit dimensions)
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- **Status:** `extracted`
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## agentskills-using-scripts
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- **URL:** https://agentskills.io/skill-creation/using-scripts.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Using scripts in skills — one-off commands, self-contained scripts with inline dependencies, designing scripts for agentic use (no interactive prompts, --help, structured output, idempotency)
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- **Contributing files:** SKILL.md
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- **Status:** `extracted`
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## agentskills-quickstart
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- **URL:** https://agentskills.io/skill-creation/quickstart.md
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- **Research doc:** plugins/kyberforge/docs/research/docs/agentskillsio/sources.md
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- **Description:** Step-by-step guide to creating a first skill (roll-dice example), how discovery/activation/execution work in practice
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- **Contributing files:** (none — creation guide not directly informing audit criteria)
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- **Status:** `extracted`
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