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Anchor Intake Agent Skill

Interrogate a written engineering implementation brief before work starts. Use when a user brings a ticket, PRD, design note, or substantive engineering task brief and wants to begin implementation planning; force every fixed rubric element to be accounted, cite present/weak claims against the brief, surface gaps, solution-as-goal traps, contradictions, and questions, then emit an intent-level plan. Do not use for bare one-line requests, non-engineering artifacts, code diff review, bug fixing, or execution itself.

1.3k tokens
context cost
SKILL.md, read when the skill is used
6
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
104
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/lynxlangya/techne --skill anchor-intake

What comes with it

73 506 bytes besides the instruction
README-CN.md
README.md
eval.md
reference.md
scripts/intake_gate.py

The instruction itself

5 sections, as written by the author

anchor-intake

Force the skipped move before execution: interrogate the written brief against a

fixed engineering implementation rubric, then plan only after gaps and weak

assumptions are visible.

Trigger Check

Use this skill when the user provides a substantial written engineering

implementation brief: a ticket, PRD, design note, or task brief with enough text

to interrogate before work starts.

Do not use it for a bare one-line request, an already precise command, a

marketing brief, research proposal, prose draft, code diff review, bug fix, or

implementation execution. For unsupported or too-thin artifacts, self-eject in

one sentence and write no .techne/plan/<slug> output. If a captured artifact

later proves unsupported, use finalize --unscopable --reason ....

Boundary test: can you point to a user-authored written artifact and ask whether

it names the engineering goal, users, measurable success threshold, scope,

non-goals, inputs, data sources, dependencies, constraints, and acceptance

method? If yes, use anchor-intake. If no, eject or ask for the brief first.

Forced Procedure

  • Capture the brief. Save the user-authored artifact verbatim. Run:

python3 skills/anchor-intake/scripts/intake_gate.py init --project <root> --plan <slug> --brief-file <path>.

  • Read the brief in full. Do not fill the rubric from memory or from the

user's surrounding chat if the value is not in the captured brief.

  • Account every fixed rubric element. For each of the ten elements, write

one disposition in .techne/plan/<slug>/intake.json:

present with citation and valueItems, present-weak with citation and a

dependent question, or gap with a question or visible modelDefault.

  • Surface traps and conflicts. Add span-anchored solution-as-goal and

contradiction findings whenever the brief implies them. Contradictions need

two verified spans.

  • Ask only dependent questions. Every question must resolve an element or

finding and carry a planDelta. Weak/gap questions must reference the weak

span/value or the missing element label.

  • Author intent-level steps. Steps are not execution yet. Each step needs an

id, dependsOnAssumptions, dependsOnSteps, verifiableOutcome, and at

least one terminal step reachable from a root step.

  • Check and repair. Run:

python3 skills/anchor-intake/scripts/intake_gate.py check --project <root> --plan <slug>.

Fix structural failures by doing the missing intake work, not by padding JSON.

  • Finalize. Run:

python3 skills/anchor-intake/scripts/intake_gate.py finalize --project <root> --plan <slug>.

Relay the generated intakeReport.json to the user, especially gaps, weak

elements, questions, solution-as-goal findings, contradictions, and warnings.

Script Contract

Artifacts are written under the target project:

.techne/plan/<slug>/
  brief.txt          # captured external artifact
  context.json       # computed by init
  intake.json        # authored by the reviewer/planner
  report.json        # computed by check
  plan.json          # computed by finalize
  intakeReport.json  # computed by finalize

Generated .techne/ output belongs to target projects. Do not commit it to this

repository.

Minimal intake.json shape:

{
  "schema": "techne.intake/1",
  "elements": {
    "data-sources": {
      "disposition": "gap",
      "questionIds": ["Q1"]
    }
  },
  "findings": [
    {
      "id": "S1",
      "kind": "solution-as-goal",
      "citation": {"offset": 16, "quote": "Build a Slack bot"}
    }
  ],
  "questions": [
    {
      "id": "Q1",
      "text": "Which data sources should the implementation read?",
      "resolves": ["data-sources"],
      "planDelta": {"adds": ["Bind implementation to the named source"]}
    }
  ],
  "steps": [
    {
      "id": "s1",
      "title": "Implement only the scoped behavior",
      "dependsOnAssumptions": ["goal-and-why"],
      "dependsOnSteps": [],
      "verifiableOutcome": "The scoped behavior can be verified by the acceptance method",
      "terminal": true
    }
  ]
}

Use reference.md for the full JSON contract, fixed rubric,

STOPLIST/RUBRIC-LABEL set, shape rules, warning semantics, and known weak spots.

Stop Conditions

  • Stop before planning if there is no substantial written engineering brief.
  • Stop before finalize if check reports blocking failures.
  • Stop and use --unscopable --reason if the artifact is not an engineering

implementation brief or is too garbled/thin to interrogate honestly.

  • Stop before executing the work. anchor-intake ends at a surfaced report and

intent-level plan; implementation belongs to the next workflow step.

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How to use it

Copy the folder

Take lynxlangya/anchor-intake from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.