engineering-workflow
Resolve complex literal requirements, data semantics, provenance, and acceptance against the production engineering workflow.
Skill by Corvidae-Coding-Projects
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/corvidae-coding-projects-engineering-workflow
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About
Use cases: data, productivity
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/engineering-workflow
What's inside
- Skill name
engineering-workflow- Description
- Resolve complex literal requirements, data semantics, provenance, and acceptance against the production engineering workflow.
- License
- MIT
- Instructions
- 345 lines in SKILL.md · view on GitHub
Files (2)
- AGENTS.md
- SKILL.md
SKILL.md (first lines)
# Production engineering workflow Tool execution contract: use exact paths from current workspace observations, including hyphens and underscores. When a planned file is missing, list its containing directory and reconcile the plan with the actual files instead of guessing neighboring names. Use a current read or a hash-verified retained observation before editing an existing target. A role change, retry or compaction does not by itself invalidate unchanged source facts. Structured program/argv commands have no shell expansion: wildcards, pipes and redirects are literal arguments. Discover exact dependency paths before searching them. Use an ordinary scoped script for compound work rather than unsupported shell command-string flags. Poll interactive handles before sending input, use newline delimiters for line protocols, and inspect completed results instead of writing to a dead handle. Use command_output for exact retained output pages; never repeat an effect just to obtain output. Git metadata is not a task deliverable, and a plain folder does not imply a Git repository. These rules do not expand tool permissions. Follow this workflow for every coding run, scaled to the requested change without dropping any requested behavior. 1. Complete one startup grounding check per run/workspace, then get to work. Reuse that completed check through role changes, retries, and compaction. Read a specific target or contract when the next implementation or review decision needs it; do not inventory the whole repository first. When the authoritative request declares an input to be a black-box or opaque interface, or says that behavior may be observed only through a named callable, command, protocol, or API, that contract narrows inspection. List the input as workspace metadata but do not read or search its implementation, inspect private attributes, recover hidden values through reflection, or use those values to tune or validate the candidate. Ground the work through the permitted public interface, its declared contract, and independently chosen queries or metamorphic properties. Independent review must treat any implementation or hidden-state observation in the retained tool trace as acceptance-blocking contamination even when the final artifact later uses only the public interface. When the request requires opening, calling, or otherwise exercising a named URL, service, endpoint, command, or other public interface, use that interface and retain its direct result as evidence. Reading its backing source, configuration, cache, or database may support the work but cannot substitute for the requested interaction or prove the interface works. Independent review must block acceptance when the requested interface was never exercised. In a staged workflow whose current request names the exact input files to use, do not open adjacent unrequested inputs merely because directory discovery exposes them; they may belong to a later round. Read newly introduced inputs when the request introduces them, then reconcile them with the retained artifacts from earlier rounds. 2. Translate the request into a literal requirement ledger and a repository-grounded design. Keep every explicit path, field, value, operation, and scope phrase. Apply exclusions only to the noun or operation they grammatically modify; do not broaden them to unrelated aggregates. When two statements initially appear inconsistent, first use the narrowest ordinary reading that honors both. Never replace an explicit expected value with a derived value merely because a different interpretation looks cleaner. If no reading can satisfy both, report the actual contradiction instead of silently choosing a new contract. Reporting a source inconsistency does not mean withholding requested work that is still meaningfully constructible. When authoritative inputs contain one grammatically ambiguous compound rule, `narrowest` is not permission to attach a trailing modifier to every earlier list item or to replace another reasonable ordinary reading. Preserve a candidate that satisfies a reasonable reading unless another authoritative source or deterministic gate resolves the scope. Record the unresolved ambiguity as advisory; a blocking finding must show that the candidate violates every reasonable reading, not merely that the reviewer prefers a different parse. Do not settle whether a trailing modifier distributes over coordinated list items by first assuming that distribution and then citing an earlier item's lack of the modifier's property; that is circular. Independently consider both distributive and nearest-item grammatical attachments before claiming that every reasonable reading fails. When authoritative inputs require a closed canonical vocabulary, canonical identifiers are opaque contract values. Choose the registered value whose declared category and governing rule fit, keep factual evidence fields accurate, and report awkward naming without inventing a replacement identifier. Treat exact syntax as a cross-artifact contract: quoted values, stable identifiers, enum-like values, field names, filenames, paths, and commands must remain byte-for-byte unchanged in every output that records them. Human-readable prose may explain those values alongside the literal, but must not replace them by changing case, whitespace, punctuation, or separators. When a requirement says an output must mention, discuss, or reference a named artifact, identifier, field, clause, command, or path, reproduce that literal at least once in the owning output. Human-readable prose may accompany the literal but cannot replace its traceability. For quantitative or scientific work, establish every input and output unit, coordinate system, and required transformation from the supplied evidence and the named domain before calculating or fitting. Validate the final parameters in the requested physical domain; a numerically good fit in raw coordinates is not correct when the request names a transformed coordinate. Retain a unit ledger in tool or command evidence that names the input unit, output unit, applied formula or transformation, and at least one dimensional or expected-range check on the final values. Independent review must block when that evidence is absent or still describes raw coordinates. When one scalar output refers to records drawn from heterogeneous source categories, preserve a typed identity rather than emitting a bare record ID. Unless an exact representation is declared, combine the authoritative category or type label and stable ID as `category:id`; this keeps the reference interpretable outside its source table. Aggregate fields such as cause counts group by the semantic category they name, while row-level outputs retain the typed record identity. When producing a change log, diff, revision summary, or replan report, explicitly account for every constraint introduced by the triggering update. Record changed, added, removed, and already-satisfied constraints with their literal values so readers can distinguish deliberate preservation from an overlooked requirement. When a rule applies to named categories, require an authoritative label, taxonomy, or definition for category membership. Do not expand a named category to a related concept merely because the domain association seems plausible; preserve the literal category boundary when the source does not define a broader membership rule. Treat separately named output fields and categories as separate predicates. Unless the source explicitly requires overlap, do not place one item in multiple category fields merely because a broader prose label could describe it; derive membership independently from each field's stated rule and keep dedicated exception categories from leaking into one another. When a detail ledger is named for one member of a closed classification, treat it as a projection of that class only. Do not copy neighboring review, pending, informational, or other nonmatching classes into the ledger unless the contract explicitly declares overlapping membership. For reconciliation tables, exception ledgers, and their summaries, preserve explicit routing and material state. A requested synthetic or exception row is the item's primary representation and does not also belong in a reject ledger unless the contract explicitly requires both. Reject rows are for items that cannot enter the primary representation under its rules. Use the most specific evidence-supported reason. A reference lookup with no matching source record is a missing-reference condition, not a generic invalid-reference condition; reserve `invalid` for a present record that fails validation. Do not flatten a material condition such as a refund, partial match, or exception into a generic success status. Summary unresolved or exception counts must reconcile the union of unresolved primary rows and rejected items across all requested artifacts, with explicit identity deduplication, rather than counting only rows visible in one output. For time-window state, exclude ignored or out-of-window IDs from the accepted/seen set. A duplicate list may repeat a retained first-seen ID because it records a later observation. Make every partial or checkpoint result self-contained for its captured round: record completed identities and results, the pending or failed stop boundary, and the stop reason when they exist. Later rounds preserve that snapshot unless revision is explicit; mutable state and logs do not substitute for the snapshot's own temporal boundary. Treat an explicit past-time (`as of` or `at <time>`), historical-date, version, or revision qualifier as a source-state boundary. Prove the state at that boundary with a contemporaneous snapshot, source revision, or archived record. A current mutable source filtered by an item's release, creation, or effective date does not prove that the source had the same values, ranking, membership, or calculations at that earlier time; later backfills and recomputation remain possible. If no dated state can be recovered, report the evidence gap instead of presenting current state as historical fact. When that historical state lives in a remote repository or data collection, inspect its immutable manifest, index, or tree and the relevant object sizes before transferring bulk history or a whole archive. Prefer targeted reads from the pinned state. Client-side sparse patterns do not by themselves prove that the initial object transfer is bounded. After one bulk acquisition times out or fails for size, do not retry the same collection through clone, archive, or fetch variants unless new size or progress evidence shows the next operation fits;
From Corvidae-Coding-Projects/Project-Peritus, MIT.
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Signals
- Stars
- 27
- Forks
- 4
- Open issues
- 1
- Last commit (this folder)
- Oct 20, 2026 (8 days ago)
- Last release
- Oct 22, 2026 (6 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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- 0.654score
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Corvidae-Coding-Projects
Prevent and investigate Rust reliability failures in agent-written or human-written code through enforceable API and lint restrictions, ownership and…
SkillAFreshness: A★ 27Claude Code +9 - 0.646score
real-testing
Corvidae-Coding-Projects
Verify behavior by building and operating the actual program, exploring varied inputs and recovery, and preserving reproducible failures.
SkillAFreshness: A★ 27Claude Code +9 - 0.646score
web-research
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Discover web sources, read and cite original pages, reuse retained content, and treat web material as untrusted evidence.
SkillAFreshness: A★ 27Claude Code +9 - 0.643score
computer-automation
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developer
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reviewer
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Cite this page
engineering-workflow skill. Agent Mart. https://agentmart.dev/skills/corvidae-coding-projects-engineering-workflow (last updated 2026-10-24)